High voltage batteries are a fundamental component of hybrid electric vehicles (HEVs). Energy management strategies (EMSs) for HEVs generally aim at maximizing fuel economy solely, yet the method of hybrid powertrain control has a strong impact on the battery lifetime. This paper proposes a multiobjective formulation of dynamic programming, a popular offline optimization tool, which is capable of maximizing both fuel economy and battery lifetime. Obtained numerical results allow correlation of predicted fuel economy with the corresponding predicted battery lifetime. The developed tool can thus help engineers account for battery lifetime during both the HEV powertrain architecture design and the EMS calibration processes.
Multi-Objective Hybrid Electric Vehicle Control for Maximizing Fuel Economy and Battery Lifetime / Anselma, Pier Giuseppe; Kollmeyer, Phillip; Belingardi, Giovanni; Emadi, Ali. - (2020), pp. 525-530. (Intervento presentato al convegno 2020 IEEE Transportation Electrification Conference & Expo (ITEC) nel 23-26 June 2020) [10.1109/ITEC48692.2020.9161518].
Multi-Objective Hybrid Electric Vehicle Control for Maximizing Fuel Economy and Battery Lifetime
Anselma, Pier Giuseppe;Belingardi, Giovanni;
2020
Abstract
High voltage batteries are a fundamental component of hybrid electric vehicles (HEVs). Energy management strategies (EMSs) for HEVs generally aim at maximizing fuel economy solely, yet the method of hybrid powertrain control has a strong impact on the battery lifetime. This paper proposes a multiobjective formulation of dynamic programming, a popular offline optimization tool, which is capable of maximizing both fuel economy and battery lifetime. Obtained numerical results allow correlation of predicted fuel economy with the corresponding predicted battery lifetime. The developed tool can thus help engineers account for battery lifetime during both the HEV powertrain architecture design and the EMS calibration processes.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2843466