Optimization of automotive battery pack casing based on equilibrium response surface model and multi-objective particle swarm algorithm

Liu, Fei; Xu, Yalong; Li, Meng; Guo, Jiale; Han, Bing

doi:10.1177/09544070221104858

Cited by 4 publications

(2 citation statements)

References 24 publications

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“…Increasing the energy density of a battery is very challenging due to the high energy density currently achieved and safety related issues. This means that it is necessary to reduce the weight of the battery pack housing to significantly improve performance [15,16]. The lightweighting de-DOI: 10.26855/ea.2022.12.004 166 Engineering Advances sign process for a battery pack system is shown in Figure 5.…”

Section: Battery Lightweightingmentioning

confidence: 99%

“…Hassan et al DOI: 10.26855/ea.2022.12.004 163 Engineering Advances [15] have combined two cylindrical holes as a unit to improve the film cooling performance at all blowing ratios. A novel combined hole was presented by Wang et al [16]. They noticed that the combined hole provides uniform film cooling performance in both downstream and lateral directions and reduced the aerodynamic loss.…”

Section: Introductionmentioning

confidence: 99%

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Innovative Technology for Quadcopter UAVs

Wang¹,

Xue²,

Li³

et al. 2023

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Quadrotor UAVs are widely used in traversal search missions due to their high space utilisation. The traditional UAV traversal search method has problems such as dead space coverage, easy interference in information return and high energy loss, which cannot adapt to the requirements of efficient search in specific scenarios. In order to solve these problems, the UAV is innovated on the basis of the existing methods, using the bull ploughing method of traversing search to improve the coverage of the target area, using remote customised protocols for map transmission to accurately return image information, and a lightweight battery design to ensure the completion of the mission in one go. Practice has proved that Fiber composite material can reduce the weight by 25%, and is the best material choice for lightweight batteries, and the UAV system with light battery meets the application requirements in terms of endurance index and can complete the requirements of flight function.

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Section: Battery Lightweightingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Innovative Technology for Quadcopter UAVs

Wang¹,

Xue²,

Li³

et al. 2023

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A survey on design optimization of battery electric vehicle components, systems, and management

Acar,

Jain,

Ramu

et al. 2024

Struct Multidisc Optim

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PB-MNSGA-II algorithm and its application for multi-objective optimization design of under-vehicle equipment

Shi,

Li,

Zhang

et al. 2024

Proceedings of the Institution of Mechanical Engineers, Part C:

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Structural damage caused to under-vehicle equipment under adverse working conditions affects the safe operation of high-speed electric multiple units (EMUs). To address the low optimization efficiency and take into account vibration fatigue in traditional under-vehicle equipment design, herein, a multi-objective optimization design method (PB-MNSGA-II) that combines particle swarm optimization-back propagation (PSO-BP) neural network and modified non-dominated sorting Genetic Algorithm II (MNSGA-II) was proposed. It can help engineers choose better equipment component thickness and achieve efficient and accurate design. First, MNSGA-II, the core content of PB-MNSGA-II, was proposed, which improved four aspects of NSGA-II: Latin hypercube sampling population initialization, adaptive crossover and mutation probability, mutation interference of Levy flight strategy, and optimal elite strategy. Then, zero-ductility transition (ZDT) series functions were employed to test MNSGA-II, thereby verifying its convergence and computational efficiency. Subsequently, utilizing the frame structure of the traction transformer (TTR) as an illustrative example, the PB-MNSGA-II approach was employed to enable multi-objective optimization. During this optimization process, the focus was on random vibration fatigue damage, thus enhancing the rationality of the optimization outcomes. After structural optimization, the mass of the TTR decreased by 20.1 kg, and the maximum vibration fatigue damage value decreased from 1.09 to 0.808, verifying the effectiveness and feasibility of the proposed method. The findings of this study provide important insights for the multi-objective optimization design of under-vehicle equipment under complex operating conditions.

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Optimization of automotive battery pack casing based on equilibrium response surface model and multi-objective particle swarm algorithm

Cited by 4 publications

References 24 publications

Innovative Technology for Quadcopter UAVs

Innovative Technology for Quadcopter UAVs

A survey on design optimization of battery electric vehicle components, systems, and management

PB-MNSGA-II algorithm and its application for multi-objective optimization design of under-vehicle equipment

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