SoC Estimation in Electric Cars using Ampere-Hour and Fuzzy Logic Approaches

In order to enhance the accuracy of the traditional Ampere-Hour (Ah) counting method for estimating the state-of-charge (SoC) of Lithium-Ion batteries in electric cars, this study integrates it with a Fuzzy Logic (FL) system. The Ah method, which estimates the SoC based on current integration, is analyzed alongside a Fuzzy Logic framework designed to reduce the error by dynamically combining the estimated SoC and reference values. The integration allows for more accurate SoC predictions under varying High-Power Pulse Current (HPPC) profiles, ranging from -100 A to 100 A. The integration of Fuzzy Logic with the Ampere-Hour (Ah) method enhances accuracy by reducing errors, leading to estimations that align closely with real-world measurements. Among the fuzzy membership functions tested, the Gaussian function provided the best performance, achieving the lowest Min-RMSE values of 3.9422 × 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−5</sup> for training and 0.06230 for validation, outperforming both the Triangular and Trapezoidal functions. This study highlights the potential of combining Ah counting with Fuzzy Logic to improve energy management in high-performance electric cars and supports the development of advanced SoC estimation techniques for sustainable mobility.