Work

Multi-objective optimization of cold plates for suppressing thermal runaway propagation within a lithium-ion battery module

Year: 2025

Type: article

Abstract: A liquid cooling system composed of three cold plates with varying cold plate thickness ( d ) and coolant flow velocity ( v ) was proposed to suppress thermal runaway propagation (TRP) within a lithium-ion battery (LIB) module which consists of 3 rows of prismatic LIBs . A 3D numerical model verified by experimental data was developed to investigate TRP behaviors of 256 cooling scenarios. To balance cooling efficiency and system mass, an Entropy-TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) optimization algorithm was employed to determine the optimal solution by considering five crucial indicators, including onset time of TR ( t on ), duration time of LIB module above critical temperature ( Δt ), system mass ( M ), total volume flow rate of coolant ( V flow ), and number of LIB rows suffering TR ( n ). Effects of d and v on these indicators were systematically analyzed. The results show that without cooling all three rows of LIBs experience TR progressively, featuring high TRP rate and long Δt . After applying the cooling system, row-to-row TRP is greatly decelerated or inhibited, depending on d and v . t on monotonously increases with larger d and v , while step-like dependency of Δt on v is detected. M only linearly depends on d , and V flow linearly correlates with d and v . Two boundary lines separating the entire simulation cases into three regions, featuring controlled, transition and uncontrolled TRP scenarios, are obtained by analyzing critical conditions. Ten optimal and ten worst cooling scenarios based on Entropy-TOPSIS optimization are identified, which indicate increasing v is more efficient for improving cooling performance than increasing d . The proposed cooling system may be applied in industrial processes to inhibit TRP, where prismatic LIB modules are used, and the drawn conclusions would provide useful insight into risk management of LIBs.

Source: Process Safety and Environmental Protection

DOI: 10.1016/j.psep.2025.107129

Authors: Hongjun Fang, Junhui Gong, Lun Li

Institution: Nanjing Tech University

Language: English

Topic: Advanced Battery Technologies Research

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $3,500