complete vehicle simulation of the prototype vehicle homer€¦ · prototype homer 31.08.2018...

Complete Vehicle Simulation of the Prototype Vehicle HOMER

Efficiency Optimization with IPG Carmaker

B.Eng. Robin Nedella | B.Eng. Timo Freilinger

Munich University of Applied Sciences

31.08.2018 1

Hydro2Motion-Team

31.08.2018 Hydro2Motion | Robin Nedella, Timo Freilinger 2

University of applied Sciences Munich

established 2009

42 members (only Students)

women‘s quota: 17%

Aerospace Eng.

Automotive Eng.

Industrial Eng.

Mechanical Eng.

Electrical Eng.

Technical Editing

Chemistry/Physics

Prototype HOMER


1 DriverMax. size 1.65mMax. weight 50 kg

Live Datatransfer via MQTTLive Monitoring of the current vehicle status

Streamlined lightweight CFRP-Body(cw∙ A = 0.06 m2)Average speed 25 km/h

200 W DC – Electric MotorSingle stage crown gear unitCurrent controlled motor control

Control and charging logic for fuel cell and electronics

450 W PEM - Fuel Cell baltic FuelCells „SuSy 450“0.4l Hydrogen Gas cylinder (200 bar)Choke to approx. 3 bar inlet pressure

H2

Electrolytic capacitors as buffer storage (27 V to 35 V)

Shell Eco-marathon (July 2018: London)


More than 20‘000 visitorsBiggest Eco-Challenger Event worldwide

More than 160 Student-Teams from over 20 countries

Competition categories: Urban ConceptPrototype

Energy types: Battery-ElectricFuel Cell (Hydrogen)Internal Combustion

Best score: 3rd (2015),Range: 603,4 km/m3

2018 score: 4th,Range: 480,6 km/m3

Average Speed: 25 km/h

➔ Efficiency Optimization with a complete vehicle simulation

Complete Vehicle Simulation


Motor

Gear

Energy supply

Driving Dynamics

Virtual driving Strategy



- operating point determines available torque and efficiency- multidimensional performance maps with testbench data:

Motor

Torque Efficiency

→ Required Power: 𝑷 =𝑼∙𝑰

𝜼



Gear - torque transmission between motor and back wheel- performance maps with testbench data:

→Data for various Configurations:- variable stages- shiftable: number of stages- different gear types- different lubricants

→ Force @ Backwheel: 𝑭 =𝑻∙𝒊∙𝜼

𝒓𝑩𝑾

T motor torquei gear transmission ratio𝜂 gear efficiency𝑟𝐵𝑊 back wheel radius

Capacitor



Energy supply

Power out

Discharged by:- Motor power consumption- Secondary consumptions (Safety Circuit etc.)

Power in

difference of energy→ new capacitor voltage

efficiency→ required hydrogen consumption

baltic FuelCells Charged by PEM Hydrogen Fuel Cell:- 450W nominal power- 21,5 – 30 V Output Voltage



Driving Dynamics- Behaviour of tires during force transmission

- Modelling of:- Behaviour in curves→ Validation at test drives

- Aerodynamics:- simulations (CFD)- wind tunnel testing- aerodynamic measurements at the test track

- Moments of Inertia (spinning parts)

- Slope downhill force: height profile of the track important



Virtual driving StrategyTrack analysis:- automatic processing of the 3D track model- special focus on altitude profile and crossprofile gradient- obstackles (e.g. manhole covers)→Optimal driving path

Smart Driver:- complex algorithms for track analysis- automated iterative simulation of vehicle control- decision rules (e.g. acceleration, steering, optimal driving path)

based on track analysis- adjusts behavior depending on sample data



Motor

Gear

Energy supply

Driving Dynamics

Virtual driving Strategy

Simulation Data:→ Hydrogen Consumption→More than 150 other parameters for all timesteps→ Analyze behavior of Vehicle

Validation of Simulation: Test Track


- Training for Drivers

- Testing the Vehicle under real conditions

- Collection of sample data to test sensors, telemetry and communication with the driver

Problem: track data unknown→ no Validation possible

→no vehicle optimization

→ suitable for functional testsand data collection only

Validation of Simulation: Test Bench


Torquemetershaft

Torque /Rotational speed

Target valuesTest benchcontrolling

Actual valuesSimulation Datafrom complete

vehicle simulation

Automated Driver:Vehicle control software

Control Loop virtual track

More than 150 parameters:- Vehicle speed- Calculated driver input- Fuel cell behaviour- …

➔ fully automated test drive on test bench➔ testing of different vehicle and strategy setups

Validation of Simulation: Test Bench


Torquemetershaft

Torque /Rotational

speed

Target values

Test benchcontrolling

Actualvalues

Simulation Datafrom complete

vehicle simulation

Automated Driver:Vehicle control

software

Simulation: 463 𝑘𝑚

𝑚3

Test Bench: 381 … 393 𝑘𝑚

𝑚3

Update ofSimulation ParametersValidation results:

→ after 9 Iterations converged➔ Simulation: 424 𝑘𝑚

𝑚3

➔ less than 8% Difference

The Race: Shell Eco-marathon London


4 Attempts: Validation of Simulation under real Conditions→Simulation: 424 ൗ𝑘𝑚

𝑚3

→1st Attempt: 415 ൗ𝑘𝑚𝑚3

→2nd Attempt: 399 ൗ𝑘𝑚𝑚3

➔Reliability shown!

➔Risky Setup Changes with less failure margin(16% less Hydrogen Consumption calculated)→Simulation: 491 ൗ𝑘𝑚

𝑚3

→3rd Attempt: 481 ൗ𝑘𝑚𝑚3

➔4th Place @ Shell Eco-marathon 2018

Current State


Matlab/Simulink Model by Hydro2Motion Vehicle Data included in Carmaker- Physics self-modeled- Vehicle self-modeled

→ Total knowledge and control over the behaviour→ Easy way to calculate Strategy by inserting GPS data

- Physical model given- Update actual vehicle parameters

→ Difficulties if special values required (e.g. tire model)→ Advantage of physical model

Outlook


Fusion of Carmaker and Matab-Model

→ Combine advantages of both!

→ Insert Simulink-Blocks in Carmaker

→ HIL-Test Bench including steering

→ Driving Simulator: Visulization with Carmaker

Contact us

B.Eng. Robin Nedella

CEO, Racing Engineer

[email protected]

+49 176 97618954


B.Eng. Timo Freilinger

Teamleader „Fuel Cell“, Racing Engineer

[email protected]

+49 1520 3640149

http://www.hydro2motion.com/[email protected]

University of Applied Sciences Munich

mailto:[email protected]


http://www.hydro2motion.com/


http://hm.edu/

complete vehicle simulation of the prototype vehicle homer€¦ · prototype homer 31.08.2018...

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