This paper presents an improved battery dynamic model for electric vehicles (EVs). The model is validated experimentally with four battery types and is designed to be simple to use, allowing parameters to be extracted from manufacturer discharge curves with only three points. The model is integrated into SimPowerSystems and used in a detailed simulation of an electric vehicle based on a fuel cell-battery power source. The results show that the model accurately represents battery dynamics. The battery model is based on a combination of experimental and electrochemical principles, with a focus on representing the battery's voltage behavior under varying current conditions. The model includes terms for polarisation voltage and resistance, as well as an exponential zone for Li-ion batteries. The model is adapted for different battery types, including lead-acid, NiMH, NiCd, and Li-ion, with specific equations for discharge and charge behaviors. The model's parameters are extracted from manufacturer discharge curves, with three key points used to determine the battery's characteristics. The model is validated experimentally for four battery types, showing good agreement between simulated and real-world data. The model's accuracy is within ±5% for most SOC ranges, with some limitations due to the absence of the Peukert effect. The model is applied to a fuel cell electric vehicle (FCV) simulation, demonstrating its ability to accurately represent the dynamic behavior of the battery during charge and discharge cycles. The model is integrated into a multi-domain simulation environment, allowing for the design and optimization of the vehicle's energy management system. The simulation results show that the model can accurately predict the vehicle's performance under various operating conditions, including acceleration, cruising, and deceleration. The model's ability to represent the battery's dynamic behavior is crucial for the design and optimization of EV systems. The model is validated against real-world data, showing good agreement with experimental results. The model's parameters are extracted from manufacturer discharge curves, making it a practical and efficient tool for battery modeling in EV applications. The model's integration into SimPowerSystems enables detailed simulations of EV systems, contributing to the development of more efficient and reliable electric vehicles.This paper presents an improved battery dynamic model for electric vehicles (EVs). The model is validated experimentally with four battery types and is designed to be simple to use, allowing parameters to be extracted from manufacturer discharge curves with only three points. The model is integrated into SimPowerSystems and used in a detailed simulation of an electric vehicle based on a fuel cell-battery power source. The results show that the model accurately represents battery dynamics. The battery model is based on a combination of experimental and electrochemical principles, with a focus on representing the battery's voltage behavior under varying current conditions. The model includes terms for polarisation voltage and resistance, as well as an exponential zone for Li-ion batteries. The model is adapted for different battery types, including lead-acid, NiMH, NiCd, and Li-ion, with specific equations for discharge and charge behaviors. The model's parameters are extracted from manufacturer discharge curves, with three key points used to determine the battery's characteristics. The model is validated experimentally for four battery types, showing good agreement between simulated and real-world data. The model's accuracy is within ±5% for most SOC ranges, with some limitations due to the absence of the Peukert effect. The model is applied to a fuel cell electric vehicle (FCV) simulation, demonstrating its ability to accurately represent the dynamic behavior of the battery during charge and discharge cycles. The model is integrated into a multi-domain simulation environment, allowing for the design and optimization of the vehicle's energy management system. The simulation results show that the model can accurately predict the vehicle's performance under various operating conditions, including acceleration, cruising, and deceleration. The model's ability to represent the battery's dynamic behavior is crucial for the design and optimization of EV systems. The model is validated against real-world data, showing good agreement with experimental results. The model's parameters are extracted from manufacturer discharge curves, making it a practical and efficient tool for battery modeling in EV applications. The model's integration into SimPowerSystems enables detailed simulations of EV systems, contributing to the development of more efficient and reliable electric vehicles.