A Fuzzy Adaptive Control Algorithm Based on an Equivalent Consumption Minimization Strategy for a Hybrid Electric Vehicle

Against the backdrop of the global energy crisis, hybrid vehicles offer greater energy saving potential. The equivalent consumption minimization strategy is an effective way to achieve energy savings for hybrid electric vehicles. This paper presents a fuzzy adaptive control method based on the equivalent consumption minimization strategy. To obtain a better SOC trajectory and lower equivalent fuel consumption, an adaptive adjustment algorithm for the equivalent fuel factor was designed, which incorporates a penalty function and a fuzzy adaptive method that accounts for SOC tracking errors. To verify the effectiveness of the proposed algorithm, this paper established a model of an HEV (hybrid electric vehicle) in Simulink and compared the proposed algorithm with the rule-based energy management strategy and the PI-based adaptive ECMS energy management strategy under different operating conditions. Compared with the rule-based and PI-based strategies, the proposed method improves the fuel economy by 1.01–4.64%, and the terminal SOC deviation is reduced from 0.0568–0.0619 to 0.0002–0.0010 under the UDDS and NYCC conditions.