Aging-aware co-optimization of battery size, depth of discharge, and energy management for plug-in hybrid electric vehicles

Abstract

Plug-in hybrid electric vehicles (PHEVs) have a large battery pack, and the depth of discharge (DOD) significantly affects the battery longevity. In this paper, the battery degradation is considered in the co-optimization of battery size and energy management for PHEVs using convex programming. The impact of DOD on battery degradation and energy management is also investigated. The cost function consists of fuel consumption, electrical energy consumption, and equivalent battery life loss. A real-world speed profile collected from the urban city bus route up to about 70 km is used as an input to evaluate the proposed method. The results suggest that, for both cases with and without battery degradation, the total cost curve with respect to the preset final state of charge (SOC) is an upward parabola, where the optimal DOD can be identified, and the optimal battery size and energy management can be determined. The results also show that, with an initial SOC of 0.9, the proposed method can reduce the total cost by 3.6 CNY compared to other existing studies with the fixed final SOC. Moreover, a sensitivity analysis is conducted to explore the effect of battery price and initial SOC on the optimal DOD and total cost.