Fuel Cell Simulation with DYNA4
Case Study Fortis Saxonia

Fuel Cell Simulation with DYNA4

The Fortis Saxonia Team at Chemnitz University of Technology develops hydrogen-powered vehicle prototypes and competes in races with them. Fortis Saxonia uses polymer electrolyte fuel cells for this purpose. The goal in the competitions is to minimize hydrogen consumption.

Customer Quote

"We implemented the DYNA4 fuel cell model to validate and calibrate the temperature and airflow controller of our fuel cell stack. The simulation results correlated, even in transient phases, very well with measurements taken from our test bench and from real driving laps."
Nico Junghanns, Drivetrain Development, Fortis Saxonia e.V., April 2021

The Challenge

H2 consumption optimization under real racing conditions

To achieve this, the control of the fuel cell is optimized, among other things. The fuel cell fan control is particularly important as a control variable, since it simultaneously supplies the oxidant oxygen for the reaction process and sets the optimal fuel cell temperature.  Measurement-based optimization is time-consuming and is instead carried out in advance using SIL (software-in-the-loop). For this purpose, the cell behavior during a vehicle race must be represented realistically and the fuel cell model has to be real-time capable and sufficiently accurate.

The Solution

DYNA4 with fuel cell model

Validation of the fuel cell model: measured data in blue,  simulation in red.
Validation of the fuel cell model: measured data in blue, simulation in red.

DYNA4 offers a comprehensive and modular Simulink model environment for vehicle simulation.
A DYNA4 vehicle model including fuel cell has been validated on the basis of measurement data (see validation) and then used for virtual races.

Crucial to successful optimization is a physical fuel cell model. This approach is used for the cell voltage:

Polarization curve of a fuel cell
Polarization curve of a fuel cell

The voltage curve under load depends, in a highly idealized way, only on the current (see polarization curve). Under racing conditions in particular, however, the dependencies are much more complex, since the cell temperature, among other things, plays a major role. By parameter fitting based on measurement data, the real voltage curve with its partly highly nonlinear equation components can be successfully reproduced. A heat balance model from classical fluid mechanics is used as the temperature model.

The Advantages

  • Optimization of the ECU code via simulation 
  • Reduction of time-consuming measurement runs or race evaluations
  • Time savings when optimizing fuel cell efficiency via fan control
  • Flexible architecture of the simulation model thanks to modular Simulink libraries

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Are you interested in fuel cell system simulation? Then let's talk!

Felix Beygang
Helping to simplify closed-loop simulations. Fom MIL, SIL to HIL.

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