An effective battery thermal management system (BTMS) is of great significance to ensure the safety and efficiency of lithium-ion batteries (LIBs). Both the temperature properties and lightweight are essential to the BTMS in electric vehicles. To fulfill these targets, a direct contact liquid-cooling system with multichannel is designed for the LIB module, and the simulation model is established and validated experimentally. The single-factor analysis is performed to explore the individual influence of different variables, and the comprehensive effect is conducted by the gray relational analysis. Furthermore, three surrogate models, including the response surface model, the Gaussian process model, and the radial basis function model, are conducted to parameterize the temperature behavior. On this basis, the multiobjective optimization functions are established and optimized by considering the maximum temperature, temperature difference, and accessories mass ratio. The results suggest that the optimized liquid-cooling system achieves high cooling efficiency and is lightweight compared with other liquid-cooling systems. The maximum temperature can be controlled below 36 °C, while the temperature difference is limited to 0.65 °C at a 3-C discharge rate. Besides, the accessories mass ratio of the battery module is declined to 10.25%.

Battery performance will be dramatically reduced at low temperatures. To solve this problem, a hybrid self-heating method (HSHM) for batteries used at low temperature is proposed. The HSHM owns features of low cost, high temperature rise rate, low energy loss, etc., which has the potential to be widely used to heat batteries. The physical and electric configuration of the HSHM is designed, and the working principles are analyzed. The heating strategy of the HSHM is then introduced to illustrate the heating performance. To validate the proposed method, the experimental workbench is established. Experimental results show that even with smaller heating current, the heating speed of the HSHM is faster, and less energy is needed to heat the battery. Compared with the traditional self-heating method, the performance of the HSHM is improved by 1.3 times for the temperature rise rate and improved by 55.6% for the energy loss rate, respectively.

In order to avoid high-temperature and large rate discharge impact on the performance of battery modules, a microchannel liquid cooling battery thermal management system (BTMS) and BTMS virtual model of the microchannel structure based on digital twin (DT) is proposed. On the basis of accurate virtual simulation model, the computational fluid dynamics (CFD) model and the Gaussian process regression algorithm were combined to drive the optimization process in order to improve the cooling capacity of the system. The results show that the microchannel plates can greatly enhance the cooling capacity of the direct cooling system and effectively improve the uniformity of the coolant. The width of the microchannel plates and the side spacing actually represent the amount of coolant flowing through the inside and outside of the battery module, which significantly impacts the maximum temperature and maximum temperature difference. Increasing the coolant flow can only effectively improve the cooling capacity of the module to a limited extent. Gaussian process regression based on the DT virtual model is more suitable for analyzing the interaction between multiple factors and obtaining global optimization results. After optimization, the maximum temperature and the maximum temperature difference of the system are reduced by 4.02 °C and 5.05 °C, respectively. The proposed structure and method are expected to provide insights into the design and development of battery thermal management systems.

Temperature inconsistency is inevitable during the battery operation, which has a significant impact on its performance. To quickly predict the temperature distribution in a battery cell, a three-heat-source electro-thermal coupled model is proposed in this article. The temperature of four feature regions in a battery cell can be determined in short time, which is potential to be implemented online. In addition, the distributed equivalent circuit model is proposed to calculate the heat generated by different heat sources. To identify the parameters of the electrical and thermal submodels, the experimental test bench is established, and the parameterizations under different conditions are carried out. In addition, the transient parameters, including the internal resistance and entropy coefficient, are adjusted with different state of charges (SOCs) and temperature. Finally, the validity and robustness of the proposed model are demonstrated through various tests of different operating conditions. The results illustrate that the uneven surface temperature distribution of the battery cell can be estimated fast, in less than 1 s. The error deviation of the proposed model is less than 1.4 °C under different conditions.