Empirical analysis of intelligent charging Decisions: Boosting efficiency for electric trucks

IF 7.7 1区工程技术 Q1 ENVIRONMENTAL STUDIES Transportation Research Part D-transport and Environment Pub Date : 2025-02-01 Epub Date: 2025-01-02 DOI:10.1016/j.trd.2024.104572

Qiujun Qian , Mi Gan , Xiaoyuan Yang

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Abstract

This study explores the benefits of intelligent charging decisions over manual ones for battery electric trucks (BETs), offering valuable insights to policymakers for promoting BET adoption. Specifically, this study proposes three distinct models: spontaneous charging, prospect theory-based charging, and reinforcement learning-based charging, each reflecting the behaviors of ordinary, rational, and intelligent drivers, respectively. We used actual freight transportation data from China’s Southwest region to simulate BET travel scenarios. The experimental results indicate that, compared to the spontaneous charging strategy, the prospect theory-based strategy can reduce charging costs to a certain extent, and the reinforcement learning-based strategy delivers a more pronounced benefit, with a 9.75% reduction in costs and a 14.71% reduction in time. Sensitivity analysis of charging station configurations showed that intelligent charging minimizes infrastructure needs. This highlights the economic and practical advantages of intelligent charging strategies, indicating their ability to enhance BET travel efficiency, which encourages broader adoption.

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智能充电决策的实证分析：提高电动卡车的效率

本研究探讨了纯电动卡车（BETs）的智能充电决策相对于手动充电决策的好处，为政策制定者促进智能充电决策的采用提供了有价值的见解。具体而言，本研究提出了自发充电、基于前景理论的充电和基于强化学习的充电三种不同的模式，分别反映了普通司机、理性司机和智能司机的行为。我们使用中国西南地区的实际货运数据来模拟BET旅行场景。实验结果表明，与自发充电策略相比，基于前景理论的充电策略可以在一定程度上降低充电成本，而基于强化学习的充电策略效果更为明显，充电成本降低了9.75%，充电时间减少了14.71%。充电站配置敏感性分析表明，智能充电使基础设施需求最小化。这凸显了智能充电策略的经济和实用优势，表明它们能够提高BET出行效率，从而鼓励更广泛的采用。

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来源期刊

Transportation Research Part D-transport and Environment 工程技术-运输科技

CiteScore

14.40

自引率

9.20%

发文量

314

审稿时长

39 days

期刊介绍： Transportation Research Part D: Transport and Environment focuses on original research exploring the environmental impacts of transportation, policy responses to these impacts, and their implications for transportation system design, planning, and management. The journal comprehensively covers the interaction between transportation and the environment, ranging from local effects on specific geographical areas to global implications such as natural resource depletion and atmospheric pollution. We welcome research papers across all transportation modes, including maritime, air, and land transportation, assessing their environmental impacts broadly. Papers addressing both mobile aspects and transportation infrastructure are considered. The journal prioritizes empirical findings and policy responses of regulatory, planning, technical, or fiscal nature. Articles are policy-driven, accessible, and applicable to readers from diverse disciplines, emphasizing relevance and practicality. We encourage interdisciplinary submissions and welcome contributions from economically developing and advanced countries alike, reflecting our international orientation.