Adaptive Equivalent Consumption Minimization Strategy with Enhanced Battery Life for Hybrid Trucks Using Constraint of Near-Optimal Equivalent Factor Bounds

The equivalent factor (EF) of adaptive equivalent consumption minimization strategy (A-ECMS) has a direct impact on the performance of hybrid electric trucks (HETs). Although EF on the state of charge (SoC) can effectively achieve fuel economy and SoC maintenance, battery life issues still need to be considered. Battery replacement costs are extremely high, directly affecting the operational costs of HETs. Thus, A-ECMS with enhanced battery life (A-ECMS-EBL) is proposed. Firstly, the near-optimal boundary of EF is determined to ensure the fuel economy of A-ECMS-EBL by analyzing the working mechanism of the HET powertrain. Secondly, a new EF calculation method is developed to enhance battery life. This method utilizes accelerator pedal opening (APO) feedback to optimize the power distribution between the engine and battery under high load conditions, thereby reducing the ratio of battery output power and number of battery cycle (NBC). Finally, the simulation results show that under typical cycle conditions, the equivalent fuel consumption (EFC) of A-ECMS-EBL increased by only 2.3% compared to the dynamic programming (DP), decreased by 1.1% compared to the A-ECMS, and the NBC significantly decreased by 6.12%. The results indicate that A-ECMS-EBL has significant advantages in improving fuel economy and enhancing battery life.