Study on coordinated control strategy for auxiliary power units in range-extended electric vehicles

Abstract

This paper presents a novel fuzzy adaptive PI coordination control strategy for the Auxiliary Power Unit (APU) in range-extended electric vehicles (EREVs) to enhance dynamic and steady-state performance during power tracking. An improved genetic algorithm is utilized to optimize the PI controller's parameters, focusing on faster convergence. A fuzzy reasoning algorithm is then employed to dynamically adjust the APU's control parameters, achieving adaptive control during power tracking. Experimental verification is conducted through bench tests, where dynamic response characteristics and power change rates of the APU are evaluated. Comparative simulations with traditional control methods demonstrate that the proposed strategy significantly improves the APU's dynamic response, offering better real-time adaptability and steady-state accuracy, effectively addressing challenges posed by power variations.