Adaptive supervisory control strategy of a fuel cell/battery-powered city bus

This paper presents an adaptive supervisory control strategy for a fuel cell/battery-powered city bus to fulfill the complex road conditions in Beijing bus routes. An equivalent consumption minimization strategy (ECMS) is firstly proposed to optimize the fuel economy. The adaptive supervisory control strategy is exploited based on this, incorporating an estimating algorithm for the vehicle accessorial power, an algorithm for the battery charge-sustaining and a Recursive Least Squares (RLS) algorithm for fuel cell performance identification. Finally, an adaptive supervisory controller (ASC) considering the fuel consumption minimization, the battery charge-sustaining and the fuel cell durability has been implemented within the hybrid city buses. Results in the “China city bus typical cycle” testing and the demonstrational program of Beijing bus routes are presented, demonstrating that this approach provides an improvement of fuel economy along with robustness and ease of implementation. However, the fuel cell system does not leave much room for the optimal strategy to promote the fuel economy. Benefits may also result in a prolongation of the fuel cell working life, which needs to be verified in future.