In recent years, the Li-ion batteries have received substantial consideration for the use of electrical vehicles and mobile electronics because of its excellent life span and high specific energy. It is necessary to connect the battery cells in series or parallel to obtain the essential power. In such cases, certain safety issues namely heat dissipation and rise in temperature must be taken into consideration. The excess temperature in Li-ion batteries affects the working performances to a very large extend. To address such issues, this paper proposes a TSSR based battery thermal management system using ANSYS FLUENT to obtain optimal battery spacing. The tunicate swarm as well as the search and rescue optimization algorithms are combined together to form a tunicate swarm search and rescue (TSSR) algorithm. Here, the battery spacing is optimized by employing TSSR optimization algorithm thereby minimizing the rate of heat transfer in the battery packs independent of specific heat capacity. The CFD model is employed since it plays a significant role in the simulation of battery temperature distribution to examine the battery thermal management system (BTMS). Finally, 10 different test functions are applied to the proposed TSSR algorithm to demonstrate its efficiency and applicability. The performance evaluation and the comparative analysis are carried out and the results reveal that the proposed approach provides optimal battery spacing thus the cooling performances of the battery packs are enhanced.

This study presents a bionic structure-based liquid cooling plate designed to address the heat generation characteristics of prismatic lithium-ion batteries. The size of the lithium-ion battery is 148 mm × 26 mm × 97 mm, the positive pole size is 20 mm × 20 mm × 3 mm, and the negative pole size is 22 mm × 20 mm × 3 mm. Experimental testing of the Li-ion battery’s heat generation model parameters, in conjunction with bionic structure and micro-channel features, has led to the development of this innovative cooling system. The traditional bionic liquid cooling plate’s structure is often singular; however, the flow path of the liquid cooling plate designed in this paper is based on the combination of the distribution of human blood vessel branches and the structure of insect wing veins. The external dimension of the liquid cooling plate is 152 mm × 100 mm × 6 mm (length × width × height). Utilizing numerical simulation and thermodynamic principles, we analyzed the heat transfer efficacy of the bionic liquid cooling module for power batteries. Specifically, we investigated the impact of varying coolant flow rates and the contact radius between flow channels on the thermal performance of the bionic battery modules. Our findings indicate that a liquid flow rate of 0.6 m/s achieves a stable maximum surface temperature and temperature differential across the bionic battery liquid cooling module, with a relatively low overall system power consumption, suggesting room for further enhancement of heat transfer performance. By augmenting the contact radius between flow channels, we observed an initial increase in the maximum surface temperature, temperature differential, and inlet–outlet pressure differential at a flow rate of 0.2 m/s. However, at flow rates equal to or exceeding 0.4 m/s, these parameters stabilized across different design Scenarios. Notably, the pump power consumption remained consistent across various scenarios and flow rates. This study’s outcomes offer valuable insights for the development of liquid-cooled battery thermal management systems that are energy-efficient and offer superior heat transfer capabilities.

In order to improve the braking energy recovery performance of pure electric vehicles, an optimized fuzzy regenerative braking control strategy was proposed based on the Sparrow Search Algorithm (SSA) for front-drive pure electric vehicles. Intelligent algorithms were integrated with Kamm circle constraints to redesign the optimal braking force distribution curves for the front and rear axles. The fuzzy logic controller employs SSA to determine the optimal proportional coefficient of regenerative braking force for the front wheels under various driving conditions. The stability was assessed by the Lateral Load Transfer Ratio (LTR). And a comprehensive evaluation index composed of braking energy recovery rate, driving range contribution rate, and energy saving rate was designed using the CRITIC method. The optimized strategy was validated through joint simulations with AVL Cruise and Simulink, and results show that the comprehensive evaluation indexes under CLTC-P and WLTC conditions are improved by 12.26% and 11.75%, respectively.