Advanced PI-Optimized Constant Current–Constant Voltage Control for Electric Vehicle Battery Charging and Discharging

Authors: Ibrahim, K.A., *Haruna, Y.S., Bakare, G.A., Baba, M.A. And Maurice, J.D.

DOI Info: http://doi.org/10.5281/zenodo.21045391

ABSTRACT

The increasing adoption of electric vehicles (EVs) has heightened the demand for reliable and efficient battery charging strategies that minimize degradation while ensuring user convenience. Although conventional Constant Current–Constant Voltage (CC–CV) control is widely used, its conventional implementation often results in prolonged charging times and potential stress on the battery. This study addresses this limitation by developing and evaluating an optimized EV battery charging system using a Direct Current to Direct Current (DC–DC) boost converter under the Constant Current–Constant Voltage profile to enhance efficiency, reduce charging duration and preserve battery State of Health (SoH). A dynamic MATLAB/Simulink model was developed to incorporate realistic lithium-ion battery dynamics and control parameters. Three metaheuristic optimization algorithms namely Teaching–Learning-Based Optimization (TLBO), Sine Cosine Algorithm (SCA) and Adaptive Sparrow Decision Algorithm (ASDA) were employed for optimal tuning of PI controller gains (Kp and Ki). The optimized controllers were evaluated against a conventional baseline controller under varying initial State of Charge (SoC) conditions 30%, 50% and 70%. Simulation results demonstrated that all approaches achieved complete charging to 100% SoC while maintaining SoH above 98.5%. The optimized controller exhibited competitive charging performance and stable SoH preservation, with only marginal differences observed among the algorithms. The findings confirm that optimization improves the robustness and adaptability of CC–CV control for full-cycle EV battery operation and provides practical insight for intelligent battery management system design.

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