MAGAZINE
ISSUE 1, 2021
REVOLVE
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Dictionary
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Enquête
Inverter
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BDO
Danske Bank
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Reliability in DV
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Aerodynamic Validation
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Path Planning
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The Perfect Accumulator
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Lap Time Simulation Bertel O. Steen
Organising the Revolve NTNU Life
EDITOR IN CHIEF Mia Elisenberg T: +47 901 26 017 E: mia.elisenberg@revolve.no
GRAPHIC DESIGNER Mia Elisenberg T: +47 901 26 017 E: mia.elisenberg@revolve.no
PROJECT MANAGER Mats Schiøtz T: +47 476 36 981 E: mats.schiotz@revolve.no
COVER PHOTO By: Johan Ludvig Holst & Cecilie Nikolaisen Of: Oscar Meisal
MARKETING MANAGER Emma Karolin Stein T: +47 469 23 722 E: emma.stein@revolve.no
PRINTED BY BK Trykkpartner AS
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Revolve Aerolyze From Formula Student to Formula 1 Team 2021 Crossword
REVOLVE NTNU E: post@revolve.no Revolve NTNU, S. P. Andersens veg 3, c/o MTP Valgrinda, 7031 Trondheim, Norway
Mia Elisenberg Editor in Chief
Hello, and welcome to a new year of Revolve NTNU! Despite the ongoing pandemic, our team has been able to work safely, and in this issue of the magazine, you’ll see what we’ve been doing and learn more about how we utilise our equipment and skills to create the best Formula Student race car possible. We wouldn’t have been able to publish this magazine without the help of our amazing team members and valuable sponsors for writing the articles. So, ready, steady, read! Mia Elisenberg Editor in Chief
Dictionary The daily life of a Revolve NTNU member consists of lots of meetings and discussions, but what do all of the often used abbreviations really mean? Text by Emma Karolin Stein and Mia Elisenberg Illustration by Mia Elisenberg
DV Driverless Vehicle EV Electric Vehicle RD RevolveDagen (the Revolve Day): our annual event celebrating our amazing sponsors
FSG Formula Student Germany: the biggest formula student competition in the world
BPP Business Plan Presentation: one of the most
CAN Controller Area Network: communication
protocol for electronic devices commonly used in automotive systems
FW Front Wing of the car
important parts of the Formula Student competitions
RW Rear Wing of the car
AMS Accumulator Management System: elec-
of the low voltage system (used by the rules up until 2018)
tronic devices responsible for monitoring accumulator properties such as voltage and temperature, enable/disable the flow of current between accumulator and the rest of the car and trigger safe states if necessary
INS Inertial Navigation System: a system that
calculates velocity, direction and position without an external reference, combining data from an IMU (Inertial Measurement Unit) and GPS
SLAM Simultaneous Localization And Mapping: a method for mapping the racetrack and localizing our racecar in that map simultaneously, used in our DV
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VCU Vehicle Control Unit: uses input from the driver as well as other sensor values to calculate torque output by using the torque vectoring algorithm
GLV Grounded Low Voltage: deprecated name
HCPCB High Current Printed Circuit Board: circuit boards that interface directly with the cells cells and transmit the current between the two poles of the accumulator
ACU Autonomous Control Unit: PCB that runs
the autonomous state machine and serves as an interface between the autonomous control unit and driverless actuators Accumulator The battery of the car: our car uses high voltage (600 V)
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Inverter: A Short Introduction Text by Eskil Aaning Mogstad and Jan Ottar Seljebu Olsen Photos by Eskil Aaning Mogstad and Jan Ottar Seljebu Olsen
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n inverter is an electric converter that transforms direct current (DC) from a DC source to alternating current (AC) to an AC load. For Revolve NTNU, inverter is a collective term. We often mean all the PCBs needed to transform DC from our battery accumulator to AC for our four three-phase permanent magnet synchronous motors. Since each motor has a converter, what we call the inverter is in reality four individual inverters. The way our inverters work is by using a technique called pulse-width modulation (PWM). Each inverter consists of three half-bridges of SiC MOSFETs. With PWM, the MOSFETs are turned fully on and off, creating voltage square waves. Since the MOSFETs are entirely on or off most of the time, the MOSFETs are only in the linear area during small time frames during turn-on and turn-off. This results in the losses being as small as possible when conducting. The MOSFETs in the three half-bridges are turned on and off in a specific sequence. This results in the voltage square waves between the motors’ three phases creating a sinusoidal current with a frequency proportional to the motor RPM.
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Our inverter consists of several different printed circuit boards, or PCBs, all of which work together. The control card has the responsibility of generating the PWM waveforms for four independent inverters. It does so by using a technique called field-oriented control. The phase currents and the motor position are measured, using current sensors from LEM and absolute encoders from Heidenhain. The control card is also responsible for monitoring the motors’ and power transistors’ temperatures and communicating with the rest of the vehicle’s systems. When the lockdown in Norway began, and the Formula Student competitions were canceled, it was uncertain when we would get access to the workshop again. With no access to the workshop, the focus shifted to 2021. A big focus during the spring and summer was thus a redesign of our inverter. The main focus of the redesign was improving packaging and increasing maintainability since the previous system was lacking in these areas.
Redesigning and testing an inverter is an intricate and time-consuming process, which is why the extra time given by Covid-19 was well needed. Currently, the new power electronic board of the inverter is being tested thoroughly. For power electronics, a testing procedure is known as double pulse testing used. This test is performed at high voltages, typically 600 V DC, and thus several safety precautions have to be taken. During the double pulse-testing, there are high currents and a dV/dt of multiple volts per nanosecond being generated on the PCB. This means that it is critical to put effort into the measurement setup to have a high signal-to-noise ratio. A handy tool we use is the CS448 oscilloscope from Cleverscope. It has four fully isolated 14-bit analog channels and a very high common-mode noise rejection ratio over a wide bandwidth. The isolated inputs result in us not needing to use differential probes while still probing multiple voltages on the power electronics, giving a much higher bandwidth on the measurements than differential probes. Having high bandwidth and resolution measurements with an excellent signal to noise ratio allows us to
push on the time it takes to turn the transistors on and off, i.e. to test greater switching speeds. We want to have the MOSFET turn-on and turn-off times as short as possible to reduce the time spent in the linear area since this means less switching losses in our inverter. Even though we got a good head start on our testing, there is a lot more that needs to be done. Therefore, the primary goal of inverter development is not to make this year’s design go on the 2021 car at whatever cost but rather create a good foundation. The inverter is the most complicated self-developed electrical system we have on the vehicle and it took four years of development and testing for our first generation. Only time will tell if this year’s car will use the new or the previous inverter. Regardless, the inverter development will still continue.
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Aerodynamic Validation Text by Adrian Leirvik Larsen Photo by Adrian Leirvik Larsen
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hen designing a Formula Student car, paying close attention to the aerodynamic design and characteristics of the vehicle is very important. Having a good understanding of how the car will behave in all driving conditions, and what drag and downforce figures that are generated on track is highly beneficial for the aerodynamics, suspension and vehicle dynamic groups. A typical Formula Student race track is full of heavy braking and acceleration zones, as well as both high and low speed corners. To arrive at a design we know will behave as expected on these tracks, the Computational Fluid Dynamics (CFD) simulations performed and estimates done during the design process need to be as accurate as possible. As the aerodynamics of a Formula Student car is a very complex system, this is no easy or straightforward task.
at the fluid mechanics lab at NTNU Gløshaugen. For the 2021 car, I will develop methods for gathering data on the aerodynamic performance while driving on track during the test season. This will include pressure sensing at several locations around the car, to get a much better understanding of how the behavior on track compares to the simulated performance. Due to the complexity of the design and experiences from previous years, deviations are expected. The question is how large and how significant they are.
Knowing the weaknesses of a design is as important as knowing the strengths. Doing a thorough analysis of the aerodynamics and identifying the weak points will improve the knowledge within the team and our transfer of experience, as well as the actual design and understanding of it. The aerodynamic This year I will write my master’s thesis for the Re- design may turn out to be one of the key factors for volve NTNU team on aerodynamic validation. I Revolve NTNU to continue performing as well as will gather data on the accuracy of our CFD mod- we have done in recent years for many seasons to els through experimental testing of a scale model come! of our 2019 car Nova in the large-scale wind tunnel
Scalar scene from Star CCM+ displaying pressure contour lines.
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Supporting Student Achievements Text by Danske Bank Photo by Revolve NTNU
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anske Bank has been a proud supporter of Revolve NTNU for several years. It is a great way to show that we root for students’ achievements and that we have more to offer than just good solutions for your banking needs. We also think that the Revolve concept is super cool from the perspective of sustainability and innovation, and it is exciting to be a sponsor for the Revolve NTNU.
“Our approach towards the partnership reflects our strategy where we want to do more with, and for, our partners. A collaboration with the committed team at Revolve NTNU gives a clear signal of how we want to help support students and tomorrow’s engineers”, says Ole Kristian Hansen, Head of Marketing in Danske Bank Norway.
Gotteberg in Partner Relations, Danske Bank. At Danske Bank we want to contribute to students reaching their potential. We have therefore also partnered up with Hold, the app helping students focus and to be less distracted by their phone. Every month during the school year students can win a stipend from Danske Bank by ‘Holding’ their phone – maybe while working on the Revolve racecar – and participating in the contest in the Hold app.
Supporting professionals is part of the reason why Danske Bank also has partnerships with several unions. Tekna has over 12,000 student members and many of these study at NTNU. Therefore supporting an initiative like Revolve, which is highly relevant for the student members of Tekna, is something we take great pride in doing. “Many of the unions we cooperate with encounter the same challenge of retaining student members even after they complete their studies. Through the collaboration with Revolve we can connect the students to the business sector and unions, and work towards succeeding with this challenge”, says Johan Sponsor | 9
Power Systems: The Perfect Accumulator Text by Max M. Robertson Photos by Revolve NTNU
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he accumulator, also called the battery pack, is an essential part of a formula student race car and requires careful consideration while being designed. Every electric formula student race car possesses an accumulator; it is where the energy is stored, and it supplies electric power to the four motors on the car. The accumulator in the new car we are building consists of more than 200 battery cells and can deliver 600 V and 80 kW distributed on the four motors. In previous years, we have used between 264 and 288 cells and this year’s design is of similar magnitude.
The acceleration of a moving object is proportional to the amount of power delivered to the object. This is the reason why we would like to deliver as much power as possible to the motors. A high power output requires a high voltage output and this is the reason for having a large number of cells connected in series. The competition rules restrict us from going higher than 600 V and 80 kW. The drawback of delivering large amounts of power to the motors is that the accumulator is emptied of energy at a higher rate and it is therefore required for the accumulator to have a higher capacity. To emphasise the importance of the capacity of the accumulator, The amount of energy and power the accumulator I would like to focus on the most important event is able to store and deliver to the motors are crucial at the competition. The endurance and efficiency parameters that will determine the performance of event at Formula Student competitions account for the car. Electric power is defined as the product of 42.5% of the possible points one can score. At the current and voltage, and for the accumulator to de- event, one will drive the endurance track for 22 km liver a high power output it must be able to have as quickly as possible with a driver change halfway, a high terminal voltage and supply large amounts and it is the event that pushes the accumulator to of current. This is where the building blocks of the its limits. accumulator, the individual battery cells, enters the picture. The lithium-ion polymer (LiPo) cells An under-dimensioned accumulator will heavily that we use in our accumulator have considerably constrain the driver from driving at race pace tohigher specific energy than the lithium-ion battery wards the end of the endurance event and the team in your smartphone! This means that we can store may lose valuable points. Then why do not all formore energy in the accumulator for a given weight. mula student teams max out and design the accuEach LiPo cell delivers 3.7 V in nominal voltage, mulator with an immense amount of battery cells, and to boost the terminal voltage of the accumu- such that one is guaranteed to be able to drive the lator to 600 V peak, we implement a cell configu- endurance event at full throttle until the very last ration where the majority of cells are connected in second? The accumulator is one of the heaviest sysseries. To illustrate, we have in previous years var- tems on a formula student car. Historically, the acied cell configuration between s132p2, s140p2 and cumulator weight is more than 30% of the total car s144p2. Here, s indicates serial connections and p weight, which means that adding more battery cells indicates parallel connections. By connecting the will imply adding a substantial amount of weight. cells in series the voltages of each single cell is add- Adding more weight will require more energy to aced up, such that we can obtain a peak terminal ter- celerate the added mass. In other words, increasing minal voltage of 600 V. the capacity of the accumulator is a double-edged sword, and finding the perfect balance between
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Simulation of the temperature in the accumulator under load.
an accumulator with enough energy to complete the endurance event at race pace, and keeping the weight at a minimum, is by no means a straightforward procedure.
air-cooled system is that air is a natural insulator, meaning that it conducts heat from the battery cells poorly. Some key aspects that one needs to get right to have a well-functioning air-cooled system of the accumulator is to cool the battery cells as evenly as Designing an accumulator with a large number of possible, dimension the radiator and fan to be able battery cells creates a challenging thermal manage- to suck enough air out of the accumulator and minment problem. When current is drawn from a bat- imise air leaks. Since the intake of air into the accutery cell, the internal resistance of the battery cell mulator is in the front of the accumulator, the air causes it to generate heat, with the rate of heat being will be warmed as it flows past the cells and is subgenerated proportionally to the current squared. sequently sucked out of the accumulator at the rear. Multiply the rate of heat generated by a single LiPo As a consequence, the cells in the rear segments will cell by all the cells in the accumulator, and you have not be cooled as much as the cells in the front segthe total rate of heat being generated in the accu- ments. This is a challenge we are working on, and we mulator. In the competition rules, it is stated that have not yet found a perfect solution that does not the temperature of the battery cells is not allowed cause other problems. to exceed 60 degrees Celsius. If the temperature of the warmest battery cell in the accumulator is ap- To conclude, there are a lot of measures that need to proaching 60 degrees Celsius at any point during be taken into consideration when designing an acthe endurance event, one will have no other option cumulator. The accumulator should be able to delivthan to constrain the power output from the accu- er enough power to the motors, and we achieve this mulator and lower the pace. through a cell configuration where a large number of cells are connected in series. It is a fine balance, When we are designing the cooling system of the dimensioning the accumulator with enough battery accumulator, we use software tools to simulate the cells without adding unnecessary extra weight. Deheat flow in the accumulator as depicted in the fig- signing the accumulator with too few battery cells ure above. The accumulator consists of 6 segments will cause the driver to not be able to complete the that are further made up of 4 modules, and the ac- endurance event at race pace, and too many battery cumulator is slightly wider at the front and slims cells in the accumulator will make the car slower. down at the rear in order to fit with the shape of the Designing the accumulator with a well-functioning monocoque. To cool down the motors and the in- cooling system is another important aspect. There verter we have chosen a water-cooled system, but to are different solutions to this problem, and both an cool down the accumulator, however, we have cho- air-cooled system and a water-cooled system could sen an air-cooled system. Both air- and water cool- be feasible solutions, as they both have their clear ing systems have their advantages and disadvantag- advantages and disadvantages. Overall, we believe es, and one should choose the system that fulfills the we have made design decisions that will make the requirements of the system the most. An advantage accumulator even better than in previous years, and of an air-cooled system is that it is lighter than a cor- are confident we will produce an accumulator that responding water-cooled system. A drawback of an will accelerate us into the top! 1111
Deep Dive: Lap Time Simulation Did you know that it’s possible to write a master’s thesis for Revolve NTNU? In this issue of the magazine, we’ll dive deeper into the magic behind lap time simulation, and Torbjørn Smith from Vehicle Dynamics will guide us.
Text by Torbjørn Smith Photos by Adrian Leirvik Larsen and Torbjørn Smith
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Lap Time Simulation
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ith the competitiveness of Using lap time simulation softFormula Student showing ware, a vehicle design can be no signs of fading, teams are ex- evaluated quantitatively, with the ploring every possible avenue in unit of measurement being the search of increased performance. lap time the vehicle uses to drive For Revolve NTNU, one of these around a representative track. In avenues is the world of lap time the example of the aerodynamic simulation. Lap time simulation device, the vehicle’s aerodynamic is a wide area of research, with performance is changed to reflect many approaches, use cases and the contribution in downforce solutions. For Revolve NTNU´s from the device, and the device use, lap time simulation is the art of quantitatively corVehicle System Dynamics relating vehicle design to lap time. This is not a new concept, but it is new for Revolve NTNU as an area of research and development. With competing teams having built their own capabilities in lap time simulation for many years now, this year, Revolve NTNU decided to employ a dedicated team member to develop Figure A1. Vehicle model. lap time simulation softThe longitudinal velocities at each respective wheel centre are given by ware for the organisation. tf , 2 tr U3 = U + r , 2
tf , 2 tr U4 = U − r . 2
U1 = U + r
U2 = U − r
ity, from simple point mass models to full on multi-body dynamic models with complex drivetrain and aerodynamic models. The vehicle model is a major deciding factor when it comes to what your simulator can model. It is therefore important to recognise what physical effects are modeled in your simulator, and what effects are not modeled before you make design judgement based on the simulator. At 1439 Revolve NTNU we have started out with a planar double track model as it allows good modeling of the tire utilisation, with both load transfer and tire slip modeled. The vehicle model also includes a basic aerodynamic model using coefficients of lift and drag, together with frontal area. For the drivetrain the mandatory 80 kW limit on power is used. (A.4) For future work the vehicle (A.5) is the most important area model where capability in the simulator (A.6) can be added, and the wish list among members is long. (A.7)
Lap time simulation is a method mass is added to the vehicle mass. Similarly the lateral velocity at each respective wheel centre can be calculated as for holistically evaluating a vehiThis makes it possible to evalV = V + ar, V = V − br. cle design. Take the exampleTheseofvelocitiesuate if the aerodynamic device can be used to evaluate the longitudinal slip (κ ) at each tyre where n = 1,. . . ,4: U −ω R U −ω R an aerodynamic device: the aer- improves κ = or worsens and κ = the ,perforU U − ω Rvehicle,U by − ω R looking U odynamic device adds downforce mance of the κ = and κ = . (A.8) U U to the car, improving grip inAnd the at the change in lap time. So, how The track needs to be a representsimilarly the lateral slip angle: V V tyres, but it has a cost in terms is this done? of ative α = − For δ and the α = purposes −δ , (A.9) track. It makes little sense U U V V of weight. So, what is the net re- this article the sim- to (A.10) use the Silverstone Formula and α divided = . α = I have U U sult on the vehicle’s performance? ulator into three main parts: vehi1 track to evaluate the perforThe longitudinal and lateral tyre forces are generated by substituting these slip quantities into: F =C κ , (A.11) How many units of downforce do cle model, track and solver. mance of a Formula Student car. F = −C α , (A.12) you need to add per unit of mass? Through the work that has been where longitudinal (C ) and lateral (C ) coefficients are found using the Magic Formula model. The resultant normal load on each tyre is calculated by summing the static wheel load, and load transfers due to longitudinal and Even a seemingly simple design The vehicle model is the set of done with our in-house develdecision like this is hard to an- equations that models the vehi- oped software Revolve Analyze, swer quantitatively. This is where cle´s physical behavior. Possible Revolve NTNU has an outstandthe lap time simulation comes in. models range widely in complex- ing history of storing and using 1,2
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test data, both from testing and competitions. It is therefore a simple task to create a track center line from either odometry or GNSS data from the different competitions we have attended in the past. The solver is the part of the simulator that uses the vehicle model, and the track, to find out how fast the vehicle can navigate the track. There are several different fundamental methods to use, including steady state, quasi steady state, driver model and optimal control, and they differ widely in complexity and capability. For Revolve NTNU, a quasi steady state or QSS approach is chosen. A powerful, yet simple solver. The QSS divides the track into segments of radius and length, before solving the vehicle’s equations of motion steady state for each segment. The result is the velocity profile of the vehicle driving around the track, and from that the lap time is calculated.
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it by comparing it to actual data from competitions and test days. This is an important step, as it is important to verify the validity of the simulator. It is also important to keep in mind what is modeled in the simulator and what is not. Even a simple point mass vehicle model can be tuned to fit test data, but that does not make it a valid representation of the vehicle being modeled nor a usable tool for design problems. Lap time simulation is a new capability for Revolve NTNU, and just one of many new avenues of research and development for this year’s team. It is an exciting subject, and it is a capability, I hope, that will remain and grow at Revolve NTNU for the foreseeable future.
The last step in creating lap time simulation software is validating 15
16 | Sponsor
Bertel O. Steen in the front seat for creating new mobility services Car sharing, micro-mobility, digitalisation, urban transportation – these are examples of trends that the automotive industry is facing. Bertel O. Steen, one of Norway’s largest companies in car-related business, is continuously developing new services to ensure mobility in a smart and sustainable way for the future. Development of new services means technology, engineering and expertise – typically to be found amongst the students at NTNU! Text by Bertel O. Steen Photos by Bertel O. Steen
Sponsor | 17
Are Hjelt Chief Technology Officer at Otto The developing team of Otto is based in Trondheim. If you have any questions or want to learn more about Otto, feel free to contact CTO Are Hjelt at are.hjelt@bos.no / 99 37 09 74
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ertel O. Steen has been one of the main sponsors of Revolve NTNU since 2017. The automotive industry is undergoing major changes and it is important for Bertel O. Steen to attract new expertise.
Citroën, Opel, DS and Kia.
– To cope with the multi-brand issue, we have integrated a third-party device that can fit into any vehicle. This device makes use of the OBD plug Otto – mobility made easy and accessible to every- and enables our platform to use the same source one of communication for the different brands we Bertel O. Steen has start-ups linked to the company. have in our car fleet. The box connected to the One of them is Otto – Bertel O. Steen’s service for car OBD contains a soldered key, which tricks the car sharing and shared micro-mobility. The service is to into believing the key is within range if we send a be found in for example the municipality of Bodø, specific signal. In doing so, we can control at what the business and residential area of HasleLinje in time the user should be able to start the engine as Oslo as well as at at several housing associations. long as the car supports keyless start, Are explains.
For the customer of Otto, all the handling is operated through one app only – easy and user-friendly. But it reveals to be more tricky when it comes to the technological development.
Besides the physical key, the box includes a sim card to communicate remotely with the Otto servers as well as a Bluetooth chip to communicate locally with the user. This indicates that the user can download the Otto app, reserve the vehicle and open/close the Are Hjelt, chief technology officer (CTO) at Otto, doors within the same app. explains more: – This procedure is similar to how Mercedes– Otto has developed mobility as a service platform, Benz allows their car owners to operate the vehiwhich includes electric bikes, electric scooters as cle through their Mercedes Me app. However, with well as cars. For the cars, we need to be able to open the technology in the Otto app, we can support the and close them without a physical key. You might same protocol for numerous of different car manunot think that would be an issue since a large num- facturers. ber of cars produced today support this from the manufacturer, but the problem lies in the various technologies the different car brands use, he says. Since Otto is a company under Bertel O. Steen, the car brands that Otto offers are the ones imported by Bertel O. Steen, i.e. Mercedes-Benz, Peugeot, 18 | Sponsor
Otto provides its services at around 30 locations in Norway. You will also find Otto cars present at Kjøpmannsgata in Trondheim. Download the Otto app and check it out.
Interested crowd at the Bertel O. Steen headquarter in Lørenskog, when the Revolve-team presented the Revolve concept and displayed Nova, one of their racing cars. Sponsor | 19
20 | Sponsor
Since the car is connected to the internet through the sim card, the Otto team can also read specific data such as fuel level, mileage, GPS and speed remotely. Compared to more traditional car rental agencies, this enables Otto to calculate automatically the cost at the end of a booking. The system automatically calculates any additional mileage fee the user might have to pay, the fuel usage, toll passages and parking in spaces with license plate recognition systems. – Moving forward, we believe there is great value in the data analysis of our fleet, Are Hjelt continues. – I’ll give you an example. Let’s say a municipality uses our platform. After a certain period of use, we can have a closer look at their fleet to see if the mix between cars is optimal. Perhaps most of the travels are made within a range of 3 kilometers – could some of these trips be done by bike instead? Or are any of the cars used for the same itinerary at the same time range – perhaps carpooling could be possible here to reduce the fleet? With our solid database, we are able to detect these kind of issues, Are says. Since the Otto platform includes both the hardware and software aspect, it is crucial to have a team with diversified backgrounds – electricians, mechanics, data analysts, frontend and backend developers and product managers. – As a software developer myself, I’ve found the tasks I’m set to do absolutely thrilling! It’s not just code on a screen, I can actually see the result of my code in how the car reacts. I’m sure the students at Revolve are familiar with the feeling from their work with their racing cars, Are says enthusiastically.
The Otto service includes cars, electric bikes and electric scooters – all together or individually. In the Otto solution, the bikes and scooters have to be parked at their designated parking stand after use.
Constant focus on digital development Otto is one of the start-ups under the Bertel O. Steen wings, another one is Fleks, a service that offers flexible car subscription. Think of it as Netflix for cars. In addition to start-ups, there are numerous initiatives for improvement and development on systems like business intelligence, data analytics, IT systems, customer journey etc. within the running business of the Bertel O. Steen group. Therefore, we believe the company will provide exciting career opportunities for NTNU students Follow Bertel O. Steen on LinkedIn and check out the career site www.boskonsern.no/karriere.
www.otto.no
www.boskonsern.no
Sponsor | 21
Life can be challenging when it all revolves around Revolve NTNU, but fret not! Text by Mia Elisenberg Photos by Revolve NTNU
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evolve NTNU is notorious for requiring more hours of work per week than most student organizations in Trondheim, but when you love your job, time flies by faster than a Formula 1 pit stop. Balancing the life of being a race car creator and a student can be challenging, but fret not; let this little guide help you along the way! No matter your field of work, it is important to stay on top of your tasks. Sometimes, it can seem overwhelming, but thankfully, there are lots of digital and analog tools to help you stay on track with the project plan. Having a common project planner online helps our team get an overview of how we’re doing in terms of deadlines and smaller projects, and it lets everyone know each other’s workload at different phases of the project.
Top 3 Tips for Staying Organised
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Write down your tasks, whether that’s in an analog or digital format. Make a plan – daily, weekly or monthly or maybe even all three. Let others know if you’re struggling with keeping up, so that they can help you.
Read the enquête on the following pages to see how our team members manage their tasks.
Recommending only one organisation system would be unuseful, as each person has their own preferred way of staying à jour, and different systems work for different people. If you’re unsure whether you like writing down a master to-do list or planning by weeks, or if you like bringing a physical planner with you or just use an app on your phone, then try out a variety of systems. That way, you’re ensured to find your preferred method of organization, and mayhaps your perfect fit is a hybrid of several systems. Personally, I like using what’s called a Kanban board. This system divides all of my tasks into three sections, such that I get an overview of what tasks I have not started yet, which ones I’m currently doing, and which ones I have completed. Furthermore, I like separating my tasks in categories based on their relation to schoolwork, Revolve NTNU or personal life. Good luck finding your system!
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Enquête
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How do you organise your tasks and stay on top of your to-do list?
Which member do you think should be applauded for their dedication and work in the team?
Lars van der Lee Vehicle Dynamics
If you could be a part of another group of the team, which would you choose and why?
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What’s your guilty pleasure at the office kiosk?
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What do you do to relax and take a break from school and Revolve work?
I usually keep track of my schedule by memory. I have tried using digital to-do lists and apps, but I rarely keep them up to date. I do however use a calendar to keep track of meetings and appointments. I don’t want to point at one member, because I believe there are many more than one. We are a big team, and very dependent on everyone contributing their share of work. In general we all have a lot to learn, and I hope we can achieve our goals. This will only be possible if everyone is dedicated!
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After three seasons, I feel I have been a part of all groups in Revolve NTNU that I want to join. I have been able to be involved in most groups during many of my small side projects. I have had three very different positions, in all ranks of the hierarchy, and have enjoyed Revolve NTNU in each of them!
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Nothing beats a frozen Kinder Maxi. I always make sure at least two boxes are placed in the freezer when Usman returns from a shopping trip!
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After the 2019 season, I have had development of Revolve Analyze features as my main hobby besides my “duties”. Finding new ways to look at data from our cars is something I find really interesting, and the possibilities are endless.
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Thora Mothes
Christian Trandem
Software
Power Systems
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In the software team we make use of Github issues to keep track of our development to-do’s. Personally I like to use Google calendar for tracking tasks that need to be completed within a certain deadline. Most of our tasks are to be done ASAP, so the best way to handle them is just getting started immediately.
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Our group leader Jostein puts a lot of time into his own personal tasks as well as coordinating team efforts and helping team members that need support. He gets an applause from me!
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Autonomous systems seems like a very interesting group to be a part of! I think I would have learned a lot of interesting things and gotten to challenge myself a lot in that group.
04 05
White Monster is my ultimate go-to! Too bad they are never cold... haha.
I like spending my time online hanging with friends on discord and playing games. It takes my mind off things, and it’s a nice way to socialise with Covid-19 restrictions in place.
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I don’t. I work with a task list in my head, coming in to the office every day to start working on the thing that is most important for the day or is closest to deadline. And something unexpected always comes up where it is possible to contribute with help.
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I think we should applaude the Alumni that are still actively contributing to the team by helping out on workshops and giving general feedback on a regular basis, even years after they’ve graduated. A lot of them them work for our sponsors, so we meet them there regurarly as well. No-one mentionened, no-one forgotten.
03
I have previously been in the Chassis group and Vehicle Dynamics, and now I am in Power Systems, so it must be one of the two other mechanical groups I still have not been in, so Suspension & Powertrain or Aerodynamics.
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Godt & Blandet is good together with an F1 race, on the race weekends.
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We are able to play table tennis at the office, so to relax I enjoy playing table tennis with my colleagues. After several years in Revolve NTNU, I have become quite the expert!
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Cecilie Nikolaisen Mechatronics
01
Try to plan what I need to get done each week/day and make a priority list. To do lists are a must!
02
It’s hard to choose one since everyone works hard but I can narrow it down to Oscar Meisal (Group Leader Mechatronics) and Simen Bergsvik (Mechatronics, Accumulator, and Safety Systems). Oscar has prioritised Revolve over most things and is in my opinion among the people who uses the most time on Revolve. When it comes to Simen, he has basically had two positions (one in Mechatronics and one in Embedded) this autumn and had to work hard to finish his tasks at Embedded in the middle of the autumn testing.
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Easily Embedded Electronics. I’m already involved in the Embedded group due to my position in Mechatronics, and I think it would be cool being involved in the PCB development for the systems on the car.
04 05 26
PK (Powerking) and Twix.
I try to make dinner and watch movies with my roommates as often as I can.
Eivind Høiseth Chassis
01
I write down all of my main goals and deadlines and plan backwards to find out what needs to be done every week/day.
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I believe there are many people that qualify for this. A team this large with such ambitious goals is packed with hard-working people who all deserve praise.
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Suspension and Powertrain. I love complex mechanical parts and machining, so that group would be a lot of fun.
04 05
Fisherman’s Friend original!!
Eat, sleep, sauna, repeat.
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Trykksaker Skilt og dekor Profil- og reklameartikler Emballasje
Tungasletta 7 | 7047 Trondheim | 73 84 80 10 | firmapost@trykkpartner.no
Nova, our car from 2019, during testing this autumn
Photos by Adrian Leirvik Larsen | 29
BDO and Revolve NTNU: Innovating Together Text by BDO, Anne-Katrine Ekseth Hollum, market manager BDO MidtNord Photo by Ole M. Wold
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or BDO, cooperating with Revolve NTNU is a new breed of employees for our new teams Business chance to support the development of impor- Analytics, Robotics and Startups/Scaleups. Revolve tant technology, and at the same time help the peo- can help us find the right candidates for the future! ple behind the innovations, so they can succeed. Above all, we will continue to deliver the exceptionChange and development are key words for BDO. al client service for which we are known. Technical Since our founding in 1963, the BDO story has been excellence is a given, but our customer experience one of continuous response to our clients’ and our is embedded in our strategy and undertaken on a people’s ever-changing needs. In the subsequent truly global and local level. In that context; the rela50+ years, BDO has grown into a US$8 billion+ tionship a big cooperation like BDO can have with business, operating in 167 countries, with over Revolve NTNU in Trondheim, can help both par80 000 employees. In Norway, we are about 1700 ties evolve and reach our goals in the future. employees, and we have 70 offices countrywide, with over 43 000 customers. Our international “Why” is “People helping people achieve their dreams,” which can signal our determination to both be an integral part of the local community, and at the same time have the knowledge and platforms that can elevate the different businesses to new heights. The cooperation with Revolve NTNU is a local initiative for the BDO office in Trondheim. Trondheim is the technology capital in Norway, so supporting local tech businesses and NTNU is important to us. We are seeing some good results in making BDO generally more known and more attractive as an employer, since the cooperation with Revolve started in 2018. Amongst other things, we use the Revolve network and their digital channels to recruit a
30 | Sponsor
Photo by Mia Elisenberg | 31
With the ongoing pandemic, we had to adapt to a new way of normal, but that doesn’t stop us from having fun at the workshop!
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Photos by Cecilie Nikolaisen and Johan Ludvig Holst | 33
Driverless: Reliability & Robustness Text by Johan Ludvig Holst Photos by Marion Løkkevig
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or this year’s DV project we are pushing for reliability across our entire technology stack, improving performance, and to complete all events to reach a top three position in all competitions we attend. We are building our driverless platform on a worldclass racecar that was built from scratch right here in Trondheim. Atmos was among the best in its class when it was built in 2018, driving into a second place at Formula Student Austria. In the two years since, Atmos has been made driverless to become the most capable vehicle Revolve NTNU has ever produced!
To do this, reliability is a definite focus area. We must have a reliable vehicle that performs consistently during testing and competitions, requiring little maintenance and almost no downtime between runs. That means we need robust and verified systems that are able to withstand long days of testing and unforeseen environments at competitions. This will only be possible by achieving a lengthy and efficient test season throughout the spring and summer, therefore we are working to get testing started as early as possible. Testing is critical to identify areas that need change and iterate on systems that show weakness, make better design choices, and to help the team learn and understand how to push the race car to its limits.
One of our main goals this year is to perform across all the driverless events. This means we must be competitive within straight acceleration for the acceleration event, lateral acceleration for skidpad, dy- For the vehicle concept this year, we have gone back namic driving in an unfamiliar track for autocross, to the drawing board, choosing only the technoloand a ten-lap fast race for trackdrive. gies that we believe are most appropriate and best promote our goals. The result is that we are removing complexity in important areas, simplifying our
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sensor suite by doubling down on lidar detection, and reducing the size of the onboard computer. For autonomous software, we are clearing years of technical debt, introducing new development environments, and establishing a validation framework allowing true continuous integration. These are important initiatives to create code that is robust, reliable, and easy to maintain. All while continuing to push the evolution of our autonomous systems. Having broader areas of responsibility in the autonomous systems group is promoting the team to work more across multiple disciplines. The intention is to allow us to make improvements where they are needed the most, rather than doing optimisations in subsystems where they are not contributing to an increase in overall performance. This creates more overlap in knowledge, enables more collaboration, and furthers our understanding of the core concept central to creating autonomous race cars – ulti-
mately improving reliability, robustness, and performance. A long testing season this autumn was valuable for learning reliability. We completed the last driving test on October 31st, the last day in the test window. Learning what it takes to make the car test ready so early in the year gives us a head start for spring when everything mechanical, electrical, and autonomous needs to be ready for a long test season.
We are hard at work ensuring reliable performance throughout the entire driverless project, and are excited to see if the work we are doing now pays off for the test period and ultimately at competitions in Europe! 35
Path Planning: How to Find the Optimal Route Text by Jørgen Rosager Photos by Autonomous Systems
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or an autonomous robot to be truly autonomous it needs to be able to move itself throughout its operating environment without any human assistance. The path planning problem is the essence of this: how can the robot find the optimal path between one point and another?
distribution to obtain a result. This might seem a bit abstract, but the concept is really simple. We generate about a thousand “particles” of varying lengths. The particles in our case are just possible paths the car could take. Now we have to do the filtering part of the problem, where we weight the particles based on how realistic they seem. Particles that go off the This problem is perhaps one of the most researched track will get a low weight, while particles that go problems in AI, with lots of well known algorithms through a lot of the cones will get a higher weight. like A*, D*, RRT and more. While all of these are The next thing to do is resampling the particles good solutions, we want to focus on a specific solu- based on the updated weights. We create a normal tion: particle filters. This is the solution Revolve distribution based on the particle weights and then Driverless NTNU has developed in-house over the create new random particles based on this distribupast two years for solving the path planning prob- tion. This means that the algorithm will converge lem presented in Formula Student Driverless (FSD). towards the best particles, which is exactly what we want! The algorithm will then merge the average of The path planning problem in FSD is finding a way the best of these particles to create a path the car can to navigate the track, which consists of blue and yel- follow. low cones on each side. While this problem might seem trivial for a human, we have realised that it is This approach is very robust, as a missing or misnot that simple for a computer, especially in diffi- placed cone likely won’t alter the convergence of cult situations like hairpin turns and tight corners. the particles. As you might expect this type of planThere is also no such thing as perfect information ning might have problems planning far ahead of when talking about the real world. The input to path the vehicle, which can be detrimental to how fast planning might not include all the cones, it might the vehicle can go. We solve this by solving the path have too many cones, the position of the cones can planning problem several times, each time with inbe slightly off etc. A solution for the path planning creasingly global input. This means that we increase problem must take these into account. It must be the search space of the particles more and more to robust, but it must also be able to plan far ahead so allow for longer exploration. Our particle filter is a that the car can drive at sufficient pace to reach our carefully tuned algorithm which balances exploragoals. tion, length of planning and runtime for maximum performance. The solution Revolve DV NTNU has developed over two years takes both of these into consideration: particle filters. A particle filter is a type of Monte Carlo algorithm, which is an algorithm that depends on repeatedly random sampling from a
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This image from our simulator shows how the particle filter sends out particles on different paths and how the best converge towards the centerline of the track.
Although this is a good solution which has worked well since 2019, we want to develop as a team and push the limit of autonomous racing even further. We will therefore find a new path planner for our autonomous systems. We haven’t decided on the concept yet, but it will probably be more deterministic than our probabilistic particle filter.
Our Driverless Vehicle: Atmos.
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Software: Revolve Aerolyze Gaining knowledge from our data.
Text by Karl Halvdan Lind Photos by Revolve NTNU, Software
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ferent angle or a different cross-section. In Aerolyze, a user will be able to search for the iterations they are interested in and select both. If you are looking at a certain image from iteration 300, Aerolyze will then keep the corresponding “twin” from iteration 313 ready to display, or display the two images next to each other depending on the mode. Whenever you want a new image, you find it with keyboard shortcuts and/or using the graphical user interface, While Analyze takes sensor data from the physical and Aerolyze will keep track of the “twin” images car after it is built, Aerolyze will be used in the de- for you. sign process before the car is built. In that regard we are expanding the scope of how the software team Even with a folder structure, it is easy to understand helps Revolve to create a faster car, which is the that finding the correct pairs of images among hunoverarching goal for any group in Revolve NTNU. dreds of thousands of others is needlessly tedious and laborious when you have to do it manually. It The aerodynamics team runs hundreds of simu- is also exactly the type of work a computer excels lations of various iterations of the car before the at – time-consuming but “mindless”. Aerolyze will design is finalised. Each of those simulations gen- automate that process and free up time for the aeroerate files that are several gigabytes in size. The aer- dynamics team to do more productive work. odynamics team has written a script that can take that file and generate loads of different images from various cross-sections, angles and variables. Currently we generate approximately 1,000 such images per simulation. The problem we are solving with Aerolyze is what to do with those images after they are created, and how we can store them to enable that. ntil now, the software team has mostly been working on Revolve Analyze, our in-house developed analytics program, that takes all the sensor data from the car and turns it into useful insights for the team. That data is used to squeeze out as much performance from the car as possible. This year, we are also working on a new program which we have nicknamed Revolve Aerolyze.
Today, if you want to compare a cross-section of iteration 300 with the same cross-section of iteration 313, you have to find the folders for both iterations, find the correct image on both cars, and manually switch both images if you want to look from a dif-
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Mockups of Aerolyze UI (User Interface)
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From Formula S to Formula 1 Bo Woelfert, the 22-year old-aerodynamics engineer studying mechanical engineering, has been a member of Revolve NTNU for four years. Two years after joining our organisation, he applied for an internship in Formula 1, and guess what? He landed the job! Continue reading to find out how his journey from Formula Student to Formula 1 has been. Text by Emma Karolin Stein with Bo Woelfert Photos by Revolve NTNU, Ferhat Deniz Fors and Jiawei Zhao
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Student
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Why did you join Revolve NTNU? My main motivation was finding somewhere I could work on larger projects and follow them through, not just the odd bits and pieces that you typically get at university. The competitive environment and absolute dependence on good teamwork also appealed to me.
work is something I’m always looking forward to. It’s huge fun to present what we’ve been able to achieve since the last season, and getting an insight into the innovations other teams bring to the table.
How did you come to apply for a Formula 1 internship? I originally met engineers and students from another F1 team What is it about Revolve NTNU at the Formula Student UK comthat has made you stay for 4 petition in 2017, which made me years? aware of the opportunities for The biggest factor is the chance students in F1. When I after a litto try working with all the differ- tle over 2 years at Revolve NTNU ent subjects that make up a com- thought that I had a chance to get plete Formula Student (FS) car. an interview I started applying, Since there’s nothing that forces which turned out to be the right you to stay within the bounds of decision. your studies, Revolve NTNU has been a fantastic way to diversify What is the biggest difference my engineering skill set. Another between Formula student and aspect that I really appreciate is Formula 1? the ability to do almost anything While it’s easy to claim that the you want as long as it helps build budgets, access to technology, a better team and faster car. size of the team and format of the year are the biggest differenWhat is the biggest challenge of tiating factor, I would say it’s the being a Revolve NTNU mem- level of knowledge that makes ber? up the biggest gap. F1 engineers There are many candidates for generally heave years or decthat title, but I’d say the biggest ades of experience in their fields, challenge is always keeping one while most in FS is starting from eye on the bigger picture. It’s easy scratch. Nobody will tell you to become very focused on indi- how to design and race a race car vidual parts of the car trying to at NTNU, so you have to teach tune or optimise every last bit yourself and each other a lot out of them. The challenge is to while developing a car. always keep asking yourself “Is the way I’m spending my time Are there any similarities? the best way to build a better per- Definitely. On the theoretical side, forming car?” and if the answer it’s largely built on the same basis is no, find a better way to use that with a big human challenge in the time. middle. Your car, whether it’s an F1 or FS car, can be as fast as you What is the best part of being a want and still perform terribly if Revolve NTNU member? it’s not designed for the driver, Seeing and competing against all and the driver has to be prepared the other teams after a year’s hard to get the most out of the car. 42
The mindset is pretty similar too: create the best possible team to create the best possible car to deliver the best possible performance. Everything else is secondary. How did your time in Revolve NTNU prepare you for your Formula 1 internship? More than I had expected. My experience from Revolve NTNU was probably more useful than my knowledge from uni. There’s more than I can put into a short answer, but I’d like to mention areas such as creating readable machine and assembly drawings and tolerancing these properly, designing for manufacture and assembly, an understanding of what makes something cheap or expensive to manufacture, an understanding of race car vehicle dynamics and aerodynamics and proper CAD (Computer-Aided Design).
What has been the biggest highlight of Revolve NTNU so far? Placing 2nd overall at FSG in 2018 and winning engineering design at FSG and FSA in 2019 with our cars are absolutely the biggest highlights.
Revolve NTNU is proud to be accelerating students to become world-class engineers and is looking forward to an exciting future for Bo! 43
44 | Sponsor
Say hello to our new team! After a successful spring and autumn admission period, we’re proud to present you Team 2021.
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The Board
Organisational
Managing the organisation and the project.
Mats Schiøtz Project Manager
Johan Ludvig Holst Chief Driverless Engineer
Usman Zarar Deputy Project Manager
Emma Karolin Stein Head of Marketing & Finance
Marius von Hafenbrädl Chief Electrical Engineer
Christian Østby Chief Mechanical Engineer
Mats Erik Haugan Head of Production
Marketing
Non-technical
Getting sponsorship agreements and marketing the project.
Emma Karolin Stein Head of Marketing & Finance
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Airin Thodesen Financial Accountant
Mia Elisenberg Marketing Member
Primiita Ravibalan Marketing Member
Simon Selassie Marketing Member
Embedded Electronics
Electric Vehicle
Taking care of the low voltage systems.
Emanuela Tuon Vi Thi Tran Group Leader
Jan Ottar Seljebu Olsen Inverter Development
Viktor Korsnes Accumulator Management System
Håkon Liverud Accumulator Management System
Anna Halleraker Vihovde Safety Systems
Jostein Brovold Sensors
Daniel Vorhaug Damper Control Unit
Sivaranjith Sivarasa Vehicle Control Unit
Software
Eskil Aaning Mogstad Inverter Development
Henrik Gustavson Grytten SoC & SoH Estimation
Technical
Developing our in-house analysis software.
Jostein Tysse Group Leader
Henrik Hørlück Berg Software Engineer
Karl Halvdan Lind Software Engineer
Thora Mothes Software Engineer
Magnus Rødseth Software Engineer
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Power Systems
Electric Vehicle
Providing reliable high voltage and current.
Max M. Robertson Group Leader
Øyvind Bjåland Nordrum Accumulator CAD
Colin MacDonald Accumulator Responsible
Cristian Trandem Cooling
Audun Olsen Inverter CAD
Håvard Sutterud Wire Harness
Aerodynamics
Electric Vehicle
Using the airflow around the car to generate downforce.
Varshan Erik Shankar Group Leader
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Bo Woelfert CAD & CFD
Børge Nyland CAD & CFD
Andreas Gidske Fasteners & Production
Adrian Leirvik Larsen Validation & Simulations
Chassis
Electric Vehicle
Designing and building the monocoque.
Ronan Njøs Dunne Group Leader
Hemund Øyulvstad CAD & Ergonomics
Eivind Høiseth Impact Attenuator & Fibersim
Haakon Paaske Inserts & Simulation
Suspension & Powertrain
Benjamin Andresen Structural Equivalency Spreadsheet
Electric Vehicle
Making the mechanical design of the powertrain & suspension system of the car.
Eivind Vikne Group Leader
Sondre Audal Structural Suspension
Mathias Lien Uprights
Christian Otto Sparre Uprights
Jonas Wold Ilebakke Motors & Gearbox
Jonas Bakke Pedal Box & Steering System
Håkon T. Gulbrandsen Rims
Daniel Nilsen Vehicle Dynamics
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Vehicle Dynamics
Electric Vehicle
Taking care of the dynamic behaviour of the car.
Asbjørn Ringnes Verlo Group Leader
Marius Hamre Nordrik Adaptive Dampers
Lars van der Lee Control System Engineer
Torbjørn Smith Lap Time Simulation
Autonomous Systems
Sigrid Aunsmo State Estimation
Driverless Vehicle
Developing the logic of the driverless vehicle.
Jørgen Rosager Group Leader
Brage Imset Autonomous Engineer
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Thea Ueland Autonomous Engineer
Sander Furre Autonomous Engineer
Ola Christoffer Våge Skidpad Controler
Mathias Lund Ahrn Autonomous Engineer
Mechatronics
Driverless Vehicle
Maintaining and modifying the electrical and mechanical systems.
Oscar Øgar Meisal Group Leader
Cecilie Nikolaisen Accumulator & Embedded
Simen Bergsvik Accumulator & Safety Systems
Syver Haraldsen Accumulator & Wiring Harness
Henrik Raa Engedal CAD & Production
Nicolai Nossum CAD & Production
Drivers
Electric & Driverless Vehicle
Driving the cars during testing and competition.
Lars van der Lee Driver Coach
Mathias Lien Electric Vehicle
Herbert Wikheim Electric Vehicle
Mia Elisenberg Electric Vehicle
Ola Christoffer Våge Driverless Vehicle
Thea Ueland Driverless Vehicle
Asbjørn Ringnes Verlo Electric Vehicle
Anna Halleraker Vihovde Electric Vehicle
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Puzzle
Crossword How well do you know Revolve NTNU and race cars?
1. 2. 3. 4. 5. 6. 7.
A device that converts direct current (DC) to alternating current (AC) Our in-house developed analytics program Revolve NTNU creates an electric ____ and driverless ____ each year The type of competition Revolve NTNU competes in An approximate imitation of reality Speed with a direction The greek word for “air�
Inverter (Revolve)Analyze Vehicle Formula Student Simulation Velocity Aero
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1. 2. 3. 4. 5. 6. 7.
1. 2. 3. 4. 5. 6. 7.
Photo by Cecilie Nikolaisen and Johan Ludvig Holst | 53
embotech
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