Multi-objective benchmark for energy management of dual-source electric vehicles: An optimal control approach

This paper proposes a novel method to develop a multi-objective optimal energy management strategy (EMS) for hybrid battery/supercapacitor (SC) electric vehicles. The method is based on an alternative approach of using Pontryagin's minimum principle (alt-PMP), which is superior to dynamic program-ming in terms of computational effort while obtaining better performance. The novel multi-objective EMS allocates the battery and SC powers to minimize the batter y degradation and the SC subsystem losses. The proposed approach deduces transparent analytical forms of the optimal solutions, which have been rarely discussed in the literature. The results form a Pareto optimal (nondominated) front dis-playing the trade-offs associated with the objectives, which can serve as a benchmark to evaluate other real-time control strategies. Numerical investigations are carried out to validate the advantages of the proposed method. The benchmark role of the obtained nondominated front is illustrated by comparing it to the well-known filter-based strategy. Moreover, this study shows the conversion of the Pareto front to an ultimate utopia point corresponding to the ideal case of the SC subsystem efficiency. The proposed approach can be extended to dimensioning problems, to develop real-time EMS, and to more complex multi-source systems in future works. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

This paper presents a novel method for developing a multi-objective optimal energy management strategy for hybrid battery/supercapacitor electric vehicles based on Pontryagin's minimum principle, which simplifies computational complexity and improves performance. The algorithm allocates power between the battery and supercapacitor to minimize degradation and losses, resulting in a Pareto optimal front.