In the United States, transportation accounts for 28% of total greenhouse gas emissions. Electric vehicles are a significant step toward lowering emissions. Lithium-ion batteries are critical to the commercialization of electric vehicles; nevertheless, batteries are temperature sensitive, and sub-optimal temperatures can cause degradation, loss of power, loss of voltage, and thermal runaway. A lightweight, safe, and effective heat management system improves the vehicle's mileage, speed, safety, and longevity. The necessity for research into the effects of temperature on lithium-ion batteries and battery packs is obvious and important in order to develop electric vehicles that are widely adopted by the public. Models that quickly and accurately forecast the temperature and voltage depending on operational parameters can avoid thermal runaway, increase charging speed, prevent lithium plating, and increase cycle life.
The work consists of a thorough investigation of the temperature effect at both the cell and pack level on various battery parameters such as state of health, internal resistance, capacity and performance. Battery models based on both equivalent circuits and physiochemical models are produced and various battery pack designs are investigated. The effect of temperature on overpotential, current density, capacity and cycle life are also modeled. The writing is divided into four parts:

This section presents mathematical models for quick calculation that can be used in battery management systems (BMS) and battery thermal management systems (BTMS). This paper introduces two distinct models: an internal resistance (Rint) model and a physiological-chemical diffusion/Butler-Volmer-based partial differential 1-D model. The Rint model incorporates a relationship between internal resistance, state of charge (SOC), and C-rate. The investigations use thermocouples on both the battery's surface and tabs. At 4C, the battery temperature rose from 22.00°C to 47.40°C, while the tab temperature went from 22°C to 52.94°C. Simulation results are compared to experimental data at various C-rates (1, 2, 3, and 4C) at 22°C. Simulation findings indicate accurate temperature prediction using a simple Rint model. The reduced physio-chemical model with only three partial differential equations (PDEs) achieves comparable accuracy to the Rint model. The Rint model accurately predicts battery internal resistance using a Pearson curve and hyperbolic sine function, based on current and state of charge.

This section show cases three electrothermal equivalent circuit models with multiple input parameters (SOH, SOC, current, and temperature). The model allows us to estimate parameters like internal impedance using practical inputs, unlike traditional physiochemical models that rely on experimentally unavailable quantities like porosity and tortuosity. The study simulates the internal impedance resistance of a LiFePO4 battery at various ambient temperatures (5, 15, 25, 35, 45 °C), discharge rates (1, 2, 3C), and SOHs (90%, 83%, 65%). The internal impedance surface fit experimental observations with a Pearson coefficient of 0.945. Three thermal models incorporated the internal resistance surface model. The first two thermal models were 0D and did not account for the battery's thermal conductivity. The first model assumed simple heating from internal resistance and convective energy loss, while the second incorporated the Bernardi Equation Reversible heat term. The third model was a 2D model that retained the earlier heat source terms while adding a tab junction heating source term. The 2D model was solved with a basic Euler approach and finite center difference method. The 0D thermal models had R2 values of 0.9964 for simple internal resistance and 0.9962 for reversible heating. The R2 for the 2D thermal model was 0.996.

This paper reported experimental data and model results for a LiFePO4 cell at C-rates of 1C, 2C, 3C, and 4C and at an ambient temperature of approximately 23°C. During the experiment, thermocouples were installed on the battery's surface. Experiments were carried out at continuous current discharge. Temperature increased with C-rates on both the surface and tabs. At 4C, the battery temperature climbed from 22 °C to 47.40 °C, while the tab temperature increased from 22 °C to 52.94°C. Simulation results indicate that the cathode generates more heat than the anode, with electrolyte resistance being the dominant source of heat. Battery temperature was highest near tabs and within the battery’s internal space. The simulation of lithium concentration in the battery revealed that the anode had a more uniform concentration than the cathode. These findings can aid in the precise design and control of Li-ion batteries.

The experimental setup consisted of 7 Panasonic NCA cells connected in parallel, with each cell rated at 3.2Ah capacity. Individual cell capacities were measured and averaged, and the experimentally determined value was 3.11Ah. The arrangement has no BMS, and the batteries were allowed to equilibrate to a steady voltage at the end of discharge. The limiting current of the cells was low, posing less safety issues. The cooling method tested was ambient air cooling, with all trials taking place at an ambient temperature of around 25°C. The battery's thermal behavior was measured at six different discharge rates (constant current): 0.5C, 0.75C, 1C, 1.25C, 1.5C, and 1.75C.