Energy Management for Plug-In Hybrid Electric Vehicle Based on Adaptive Simplified-ECMS

Abstract

When searching for the optimal solution, Equivalent Consumption Minimum Strategy (ECMS) has to calculate and compare the total equivalent fuel rate of huge candidates covered all over the control domain for each time instant. Therefore, this strategy still has a heavy computation burden problem; it is a challenge for ECMS to be implemented online for real-time control. To reduce ECMS's calculation load, this paper proposes an adaptive Simplified-ECMS-based strategy for a parallel plug-in hybrid electric vehicle (PHEV). A convex piecewise function is applied to fit the total equivalent fuel rate with respect to the motor torque, which is the control variable. Then, the ECMS problem is simplified to calculate and compare only five candidates' total equivalent fuel rate to determine the optimal torque distribution. Particle swarm optimization (PSO) algorithm is applied to optimize the equivalent factor, and the MAPs of this factor under different driving cycles, driving distances and initial SOC are obtained. Based on this, the adaptive Simplified-ECMS-based strategy is proposed. Simulations were performed, and the results show that the Simplified-ECMS-based strategy can obviously shorten the calculation time compared to ECMS-based strategy, and the adaptive Simplified-ECMS-based strategy can decrease fuel consumption of plug-in hybrid electric vehicle by 16.43% under the testing driving cycle, compared to CD-CS-based strategy. A road test on the prototype vehicle is conducted and the effectiveness of the Simplified-ECMS-based strategy is validated by the test data.

Optimization and Application for Hydraulic Electric Hybrid Vehicle

“…Vehicle dynamics is used to analyze the vehicle tyre model. The angular speed (ω drive ) and the torque (T drive ) of its transmission shaft can be represented by Equations (6) and 7, where GR is the final transmission gear ratio, r is the tyre radius, η fd is the transmission efficiency, and F tire is the tyre force.…”

“…For optimization strategy, Lu et al [5] introduced the weighted-sum method and no-preference method to solve the multi-objective optimization problem of plug-in electric vehicles, and it was validated with ADVISOR software. Zeng et al [6] proposed a different strategy, Equivalent Consumption Minimum Strategy (ECMS), to solve the optimization problem of PHEV, and the Simplified-ECMS strategy could effectively shorten the calculation time. Wang et al [7] applied the Dynamic Programming for PHEV and received an approximately 20% improvement in fuel economy.…”

Energy Management Optimization of Series Hybrid Electric Bus Using an Ultra-Capacitor and Novel Efficiency Improvement Factors

“…With this EMS, evaluating the efficiency increment by the UC itself is feasible because the engine/generator is only used for the ESS charger when the SOC reaches the minimum allowance level [24]. However, considering the application principle of the efficiency improvement factors in the next section, the proposed concept is also applicable to other real-time EMSs [40][41][42][43]. The TCS algorithm is given from (17) to (19), where e S , h SOC , and l SOC , represent the engine/generator on/off switching, upper limitation of the battery SOC, and lower limitation of the battery SOC, respectively [28].…”

An Adaptive Equivalent Consumption Minimization Strategy for Plug-In Hybrid Electric Vehicles Based on Energy Balance Principle

“…This method is validated effective under a single driving condition; however, it usually cannot be qualified when the driving condition is highly mixed with different road types. Compared with the simple ECMS, the adaptive ECMS (A-ECMS) is more capable of managing energy distribution and improving fuel economy to some extent [26], [27]. In [28], [29], the A-ECMS is proposed by regulating the battery state of charge (SOC) based on linear or nonlinear control algorithms, such as the typical proportional-integral-differential (PID) controller.…”