Integrated Battery Lifetime and Energy Efficiency Driving Strategy for Electric Vehicles in Urban Environments

Continuous traffic signal intersections in urban roads significantly increase vehicle energy consumption and the frequent acceleration and deceleration spur the degradation of electric vehicles (EVs) batteries. This paper proposes an integrated battery lifetime and energy efficiency driving strategy (IBE) based on a hierarchical framework for EVs in urban roads with multi-signalized intersections. In the upper layer, vehicles take into account global information from multiple traffic signals ahead in their travel direction to determine feasible phases time at each intersection. In the lower layer, a spatial-domain-based model predictive control (S-MPC) framework is introduced to achieve optimal control of the vehicle. Simulation results indicate that the proposed IBE strategy avoids stopping at red lights and, compared to two typical constant-speed strategies, can achieve a maximum improvement of 26.6% in battery lifetime and 10.5% in energy savings.

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Publication Details

Published
2024-08-21
DOI
https://doi.org/10.1109/ccta60707.2024.10666572
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
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article

Integrated Battery Lifetime and Energy Efficiency Driving Strategy for Electric Vehicles in Urban Environments

Guodong Yin, Bingbing Li, Boli Chen, Weichao Zhuang et al.
Advanced Battery Technologies Research
article

Integrated Battery Lifetime and Energy Efficiency Driving Strategy for Electric Vehicles in Urban Environments

Guodong Yin, Bingbing Li, Boli Chen, Weichao Zhuang, Sunan Zhang, Ming-Yang Chen
article en

Abstract

Continuous traffic signal intersections in urban roads significantly increase vehicle energy consumption and the frequent acceleration and deceleration spur the degradation of electric vehicles (EVs) batteries. This paper proposes an integrated battery lifetime and energy efficiency driving strategy (IBE) based on a hierarchical framework for EVs in urban roads with multi-signalized intersections. In the upper layer, vehicles take into account global information from multiple traffic signals ahead in their travel direction to determine feasible phases time at each intersection. In the lower layer, a spatial-domain-based model predictive control (S-MPC) framework is introduced to achieve optimal control of the vehicle. Simulation results indicate that the proposed IBE strategy avoids stopping at red lights and, compared to two typical constant-speed strategies, can achieve a maximum improvement of 26.6% in battery lifetime and 10.5% in energy savings.

University College London (GB), Southeast University (CN)
Affordable and clean energy
Openalex Percentile: Top 84%
Advanced Battery Technologies Research
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