A method of combining active and passive strategies by genetic algorithm in multi-stage cold start of proton exchange membrane fuel cell

The difficulty of cold start at low temperatures has been a major technical barrier to the commercialization of proton exchange membrane fuel cells (PEMFCs). In this context, this paper proposes a strategy that combines passive and active start to achieve fast, safe, and efficient start-up at −40 °C. Firstly, a simulation model of the PEMFC system is developed using experimental data to analyze the cold start performance and energy consumption of the stack. Moreover, a multi-stage cold start strategy for heating power and current is proposed to enable the cooperative control of the positive temperature coefficient (PTC) heater and the stack. To achieve this, the dual crucial but conflicting coefficients, heating energy consumption and start-up time, are used as the optimization objectives. And the genetic algorithm (GA) is used for optimization. The results show the weighting coefficient of the optimal cold start control strategy is 0.7. Compared to the passive cold start with weighting coefficient of 0, an increase in PTC heater energy consumption of 497 kJ reduces start-up time by 32.39 % and hydrogen required for reaction by 36.17 %. Compared with other active strategies, the start time is shortened by more than 115.4s without significantly improving the energy generated by stack.