Rule-based approximate equivalent consumption minimization strategy algorithm for through-the-road vehicles energy management strategy

• A rule-based approximate ECMS algorithm is proposed for TTR vehicles. • EF rules are formulated a thorough analysis of EF, TEIT, TREFC, and SOC relationships. • The approximate algorithm reduces TEFC and computational time and maintains final SOC. This research presents a rule-based approximate equivalent consumption minimization strategy (ECMS) algorithm for energy management of through-the-road (TTR) vehicles to enhance energy efficiency with real-time computational feasibility. The approximate algorithm is developed based on the designed ECMS framework and algorithm to coordinate the torque of the internal combustion engine (ICE) and the motor according to the vehicle’s operating modes. The equivalent factor (EF) rules are formulated through offline analysis of the relationships among EF, total equivalent ICE torque (TEIT), total real-time equivalent fuel consumption (TREFC), and battery state of charge (SOC) under both fixed vehicle velocity and combined driving cycle. Based on these rules, databases incorporating actual velocity and TEIT are constructed. Compared to ECMS with the fixed charge-sustaining EFs, the proposed algorithm achieves similar or improved performance in both SOC maintenance and energy efficiency. Specifically, it reduces the total equivalent fuel consumption (TEFC) by over 11.3% under both the WLTP and CLTC with initial SOC 60%. Furthermore, it maintains a higher final SOC at the cost of less than 0.155 L in additional TEFC when the initial SOC is 30%. This performance, coupled with a significantly reduced computational time, demonstrates the approximate algorithm strong practicality and real-time applicability for onboard energy management in TTR vehicles.