Jun 28, 2025 · To address the multi-objective co-optimization challenge of lightweighting and safety in electric vehicle battery packs, this paper proposes a multi-objective optimization
Jan 1, 2015 · The bottleneck of electric road vehicles lies in the low energy density, high costs, and limited lifetime of the battery cells contained in a high-voltage battery pack. As the battery
Oct 21, 2021 · Therefore, design optimization of the battery-pack enclosure (BPE) is critical for enhanced mechanical and crashwrothiness performances. In this study, a lightweight design
Jan 21, 2025 · Many manufacturers offer best lightweight battery packs that cleverly incorporate high-density batteries and efficient circuitry to maximize energy storage within a compact design.
Jul 5, 2023 · To study an efficient lightweight method of electric vehicle power packs, the paper proposes that a hybrid method is combined with the modified Genetic Algorithm (NSGA-II), the
Jul 20, 2021 · The challenges facing electric vehicles with respect to driving range and safety make the design of a lightweight and safe battery pack a critical issue. This study proposes a
Feb 12, 2025 · Lightweight battery have now become an indispensable component in many fields. They provide power for smartphones, laptops, electric vehicles, and wearable devices, and the
Jul 15, 2020 · Firstly, structural improvement design and light alloy material replacement for high-strength steel battery pack of a pure electric vehicle were carried out, which improvd the safety
Jul 31, 2022 · 本文采用CAE 的手段, 利用soildworks 三维建模软件建立一个锂电池包的 模型后,根据电池包的实际情况设置边界条件(夹 具,力),进行有限元分析后,得出将汽车电池包轻
The design of the battery pack case integrates lightweight design and performance requirements through weight distribution, material selection, and thickness optimization. Material properties align with industry standards for battery enclosures . Detailed thickness and material distribution for each component are provided in Table 3.
The battery packs are crucial components of electric vehicles and may severely affect the continue voyage course and vehicle safety. Therefore, design optimization of the battery-pack enclosure (BPE) is critical for enhanced mechanical and crashwrothiness performances.
Additionally, modal, crash, and crush simulations are performed to validate the optimized battery pack, confirming that its crashworthiness meets safety standards. With the rapid development of electric vehicle (EV) technologies, battery pack optimization has emerged as a focal point of research.
The separation margin from the vehicle frame frequency was enhanced by 22.7 %, significantly mitigating the risk of resonance. Therefore, the multi-objective optimization results for the wall thickness of the battery pack are reliable.
This study integrates Pearson correlation analysis, RSM, and the NSGA-II to propose a multi-objective collaborative optimization framework for electric vehicle battery packs. First, modal analysis and bottom crash simulation of the battery pack are performed using Abaqus/CAE to obtain the relevant data.
To address the multi-objective co-optimization challenge of lightweighting and safety in electric vehicle battery packs, this paper proposes a multi-objective optimization framework that integrates the Pearson correlation coefficient, response surface methodology (RSM), and the non-dominated sorting genetic algorithm II (NSGA-II).
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