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

IF 7.3 1区工程技术 Q1 ENVIRONMENTAL STUDIES Transportation Research Part D-transport and Environment Pub Date : 2025-02-01 DOI:10.1016/j.trd.2024.104572

Qiujun Qian , Mi Gan , Xiaoyuan Yang

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引用次数: 0

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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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.