Multi-Objective Optimisation Method for Identifying Retired Points of Electric Vehicle Batteries

• Main Authors: Taoxiang Wang, Lixia Kang, Yongzhong Liu
• Format: Article
• Language: English
• Published: AIDIC Servizi S.r.l. 2019-10-01
• Series: Chemical Engineering Transactions
• Online Access: https://www.cetjournal.it/index.php/cet/article/view/10606

A multi-objective optimisation method to quantitatively identify retired points of electric vehicle (EV) batteries is proposed to minimise the life cycle cost (LCC) of EV batteries and the total annual cost (TAC) of energy storage systems (ESS). It features comprehensive considerations of battery capacity degradation characteristics and energy storage capacity optimisation. The effectiveness of the proposed method is demonstrated by a case study. The influence of the purchase cost and the profit of batteries in the second life are analysed. The Pareto front of LCC and TAC is given. The trade-off point is obtained when SOHre is 0.855 and the corresponding LCC and TAC are 28,742.2 USD and 7,905.5 USD. Results indicate that retired points are intensively dependent upon the optimal capacity, LCC and TAC. Both LCC and TAC can be reduced by decreasing the purchase cost and increasing the profit without changing the retired points.