4.7 Article

Application of a new type of lithium-sulfur battery and reinforcement learning in plug-in hybrid electric vehicle energy management

Journal

JOURNAL OF ENERGY STORAGE
Volume 59, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.est.2022.106546

Keywords

Battery degradation; Li-S battery; Energy management strategy; Plug-in hybrid vehicle

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The increase in vehicle ownership has led to a rapid rise in overall energy consumption. Developing new energy vehicle technologies and improving energy utilization efficiency are crucial in saving energy. Plug-in hybrid electric vehicles (PHEVs) offer a practical solution to energy shortage concerns. This study examines the application of a new lithium-sulfur (Li-S) battery in PHEVs, which is cheaper and easier to manufacture compared to conventional lithium-ion batteries. The high energy density of Li-S batteries also provides a longer range for PHEVs. The study includes a PHEV propulsion system model and evaluates the real-time performance of the Li-S battery using different energy management strategies. The new Li-S battery reduces fuel consumption by up to 14.63% and battery degradation by up to 82.37% compared to lithium-ion batteries.
The continuous increase in vehicle ownership has caused overall energy consumption to increase rapidly. Developing new energy vehicle technologies and improving energy utilization efficiency are significant in saving energy. Plug-in hybrid electric vehicles (PHEVs) present a practical solution to the arising energy shortage concerns. However, existing battery technologies restrict PHEV application as the most popular lithium-ion battery has a relatively high capital cost and degradation during service time. This paper studies the applica-tion of a new type of lithium-sulfur (Li-S) battery with bilateral solid electrolyte interphases in the PHEV. Compared with metals such as cobalt and nickel used in conventional lithium-ion batteries, sulfur utilized in Li-S is cheaper and easier to manufacture. The high energy density of the new Li-S battery also provides a longer range for PHEVs. In this paper, a PHEV propulsion system model is introduced, which includes vehicle dynamics, engine, electric motor, and Li-S battery models. Dynamic programming is formulated as a benchmark energy management strategy to reduce energy consumption. Besides the offline global optimal benchmark from dynamic programming, the real-time performance of the Li-S battery is evaluated by Q-learning and rule-based strategies. For a more comprehensive validation, both light-duty vehicles and heavy-duty vehicles are consid-ered. Compared with lithium-ion batteries, the new Li-S battery reduces the fuel consumption by up to 14.63 % and battery degradation by up to 82.37 %.

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