Equivalent Consumption Minimization Strategy With Consideration of Battery Aging for Parallel Hybrid Electric Vehicles

Bin Zhou,Amir Rezaei,Jeffrey B Burl

doi:10.1109/access.2020.3036033

Abstract

The equivalent consumption minimization strategy (ECMS) is a well-known energy management strategy for Hybrid Electric Vehicles (HEV). ECMS is very computationally efficient since it yields an instantaneous optimal control. ECMS has been shown to minimize fuel consumption under certain conditions. But, minimizing the fuel consumption often leads to excessive battery damage. This paper introduces a new optimal control problem where the cost function includes terms for both fuel consumption and battery aging. The Ah-throughput method is used to quantify battery aging. ECMS (with the appropriate equivalence factor) is shown to also minimize the cost function that incorporates battery aging. Simulation results show that the proposed aging ECMS algorithm significantly improves battery aging with little or no fuel economy penalty compared to ordinary ECMS.

Highlights

The Hybrid Electric Vehicles (HEVs), considered in this paper, have two energy sources: combustible fuel and an electric battery
Simulation Results equivalent consumption minimization strategy (ECMS) is a causal controller with a fixed equivalence factor since no information about the future driving conditions is being used to estimate λ [39]
When λ = 4/Qlhv, the aging ECMS operates in engine only mode, the battery charges at the beginning of the drive cycle, and the state of charge (SOC) remains at the upper constraint

Summary

INTRODUCTION

The Hybrid Electric Vehicles (HEVs), considered in this paper, have two energy sources: combustible fuel and an electric battery. Some well-studied energy management strategies for HEVs are rule-based control (RBC) [10], the equivalent consumption minimization strategy (ECMS) [11][12], model predictive control [13], and dynamic programming [14]. Some studies have shown that the performance of RBC is poor in comparison with strategies like ECMS or model predictive control [15]. The ECMS cost function includes fuel usage and applies a penalty for using battery power The weighting for this penalty is known as the equivalence factor. Note that the normalized Ahthroughput will be used in the battery aging term of the cost function which directly influences the optimal power split In this paper, these values have been modified to be the average values over a combination of drive cycles.

General ECMS Equivalence Factor Bounds

Aging ECMS

Conclusion and Future works