# Meta-Heuristic Optimization and Comparison for Battery Pack Thermal Systems Using Simulink
## 2 Numerical Methods for Simulink  
### Liquid Cooling Module  
The Simulink model used in this study presents a comprehensive simulation of an Electric Vehicle (EV) battery cooling system, an overall aspect of contemporary EV technology. We aimed to work with the \"sscfluids_ev_battery_cooling\" example in MATLAB shown in Figure 1. When actual speed and input values corresponding to the FTP-75 drive cycle are inputted, the model employs a liquid pump to cool the battery pack. Notably, regarding battery pack modules, many manufacturers cannot perform a direct validation due to confidentiality constraints. Therefore, to assess the thermal system, we rely on MATLAB's basic tutorial-level model to validate the optimal algorithm, whose approach seems prudent only for the study of the optimization algorithm. In this configuration, the battery packs are situated atop a strategically engineered cold plate, encompassing designed cooling channels. These channels guide the cooling liquid flow beneath the battery packs, ensuring effective heat transfer. Three-dimensional interpolated properties such as density, specific heat, specific internal energy, kinematic viscosity, thermal conductivity, etc., are also provided by Simulink. In Figure 2, data are represented in a multi-dimensional variable, including the volume fraction of each ethylene glycol. Since the data are functionalized and grouped as a graphic user interface (GUI), based on each calculation, it allows for the accessible and easy acquisition of the required values in Simulink. These data are provided based on temperature and pressure. For temperature, it can be applied from extreme low temperatures of 250 K to high temperatures of 373 K, offering a range that can be used in virtually all BTMS research contexts might affect thermal runaway [31; 32; 33]. The heat absorbed by the cooling liquid is subsequently transported to a multifunctional heating-cooling unit (HCU). Uniquely composed of three distinct branches, the HCU can switch between operating modes to both cool and heat the battery as required. The heater branch incorporates an electrical heater, produced by the battery pack, facilitating the rapid heating of the batteries in low-temperature conditions, thus ensuring an optimal performance across a wide range of environmental circumstances. As shown in Figure 1b, the radiator employs both air-cooling mechanisms, this branch offers stable temperature control when the batteries are in regular operation, enhancing both efficiency and longevity. The refrigerant system is particularly engaged for cooling overheated batteries, a critical safeguard for both safety and functionality. The heat extraction process is quantitatively represented by the amount of heat flow removed from the cooling liquid, reflecting a precise control over the thermal management process. The entire system is subjected to rigorous simulations under varying conditions, including the FTP-75 drive cycle and diverse fast charge scenarios, across a spectrum of environmental temperatures. This detailed simulation offers valuable insights into the dynamic performance and adaptability of the cooling system, contributing to the ongoing development of efficient and sustainable EV technologies. Figure 1: _Cont._  
Figure 1c illustrates the configuration of the battery pack. In the basic model presented, the pump operates independently from the battery, thereby necessitating an additional power input. Considering that battery power is depleted, as highlighted when the torque produced by the pump is multiplied by its rotational speed and then fed into the battery, we derived an optimal design strategy to minimize the battery's usage during the pump's operation. When the current value required for the FTP-75 driving cycle of the EV is entered, the battery temperature increases. The elevated battery temperature then interacts with the pump response delay control in Figure 1d, which is based on the preset temperature value, \(T_{\text{set}}\). Consequently, the pump's power is determined over time.