Multi-Objective Structural Optimization Design for Electric Excavator-Specific Battery Packs with Impact Resistance and Fatigue Endurance

Zihang Li, Jiao Qin, Ming Zhao, Minmin Xu, Wei Huang and Fangming Wu ()
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Zihang Li: School of Mechanical Engineering, Guangxi University, Nanning 530004, China
Jiao Qin: School of Mechanical Engineering, Guangxi University, Nanning 530004, China
Ming Zhao: Guangxi Liugong Machinery Co., Ltd., Liuzhou 545007, China
Minmin Xu: School of Mechanical Engineering, Guangxi University, Nanning 530004, China
Wei Huang: School of Mechanical Engineering, Guangxi University, Nanning 530004, China
Fangming Wu: Guangxi Liugong Machinery Co., Ltd., Liuzhou 545007, China

Energies, 2025, vol. 18, issue 3, 1-17

Abstract: As the issue of energy scarcity becomes increasingly critical, the adoption of electric construction machinery emerges as a pivotal strategy to address the energy crisis. During the travel and operation of electric construction machinery, the machinery-specific battery packs are subjected to long-term mechanical shocks and random vibration loads, leading to resonance and structural damage failure. To address the multi-objective optimization design issues of machinery-specific battery packs for electric construction machinery under the action of random vibration and impact loads and to enhance the fatigue life and reduce the mass of the battery pack, this paper conducts optimization design research on a newly developed battery pack for an electric excavator. Firstly, a finite element model of the battery pack is established to conduct simulation analyses on its impact resistance characteristics and fatigue life. Secondly, through a comprehensive contribution analysis method, key components are identified, with the thickness dimensions of the battery pack parts selected as design parameters. Finally, using maximum stress under mechanical shock conditions and first-order constraint mode as constraint conditions, mass minimization and fatigue life maximization are set as optimization objectives. The Box–Behnken experimental design is employed alongside a Kriging approximation model; subsequently, the NSGA-II algorithm is utilized for multi-objective optimization. The optimization results show that, while meeting the basic static and dynamic performance requirements, the mass of the optimized battery pack outer frame is reduced by 56.8 kg, a decrease of 5.75%. Concurrently, the optimized battery pack’s fatigue life has increased by 1,234,800 cycles, which is an enhancement factor of 1.65 compared to pre-optimization levels. These findings provide significant reference points for optimizing structural performance and achieving lightweight designs in electric excavator battery packs.

Keywords: battery pack; mechanical impact; fatigue life; multi-objective optimization; lightweight design (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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