The air supply system in a Fuel Cell Electric Vehicle (FCEV) provides the oxygen needed for the fuel cell to react with hydrogen. The air compressor, being the main component of the air supply subsystem, has the highest power consumption among all auxiliary loads in an FCEV. Therefore, efficient control of the air supply system is critical for improving fuel cell performance.
The air supply system has a slow response to dynamic load changes. Due to its weak transient response, an overshoot in airflow can lead to an increase in auxiliary power loss, while an undershoot can cause a delay in meeting power requirements. Thus, reducing transients is a crucial factor in improving the overall system efficiency.
In conventional control, the battery supplies additional power needed during dynamic load changes. During high dynamic load changes, there is frequent switching between the battery and the fuel cell. This frequent charging and discharging of the battery can impact its longevity.
Currently, the control of the air compressor in the fuel cell is reactive. The proposed solution aims to reduce the losses in the air compressor by predictively tuning the gain parameters of the controller and optimizing the power split between the fuel cell stack and the battery using the predicted vehicle load.
Predictive tuning helps in reducing transients in fuel cell air compressor control, ensuring smooth power transfer and minimal losses due to the air system. The proposed method uses the topography ahead information and other vehicle parameters to estimate the load. The air compressor model, coupled with predictive and adaptive tuning, suggests the controller parameters that minimize the air system losses. The switching strategy between the fuel cell stack power and battery power takes the dynamics in predicted load changes into consideration.