This paper presents a novel adaptive cell recombination strategy for balancing lithium-ion battery packs, targeting electric vehicle (EV) applications. The proposed method dynamically adjusts the series–parallel configuration of individual cells based on instantaneous state of charge (SoC) and load demand, without relying on conventional DC-DC converters or passive components. A hardware-efficient switching topology using SPDT (Single Pole Double Throw) switches enables flexible recombination and fault isolation with minimal complexity. The control algorithm, implemented in MATLAB/Simulink, evaluates multiple cell-grouping configurations to optimize balancing speed, energy retention, and operational safety. Simulation results under charging, discharging, and resting conditions demonstrate up to 80% faster balancing compared to sequential methods, with significantly lower component count and minimal energy loss. Validation using Panasonic NCR18650PF cells confirms the model’s real-world applicability. The method offers a scalable, high-speed, and energy-efficient solution for integration into next-generation battery management systems (BMS), achieving performance gains typically reserved for more complex converter-based architectures.

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The growing deployment of electric vehicles requires battery management systems that maintain cell uniformity while reducing hardware complexity and improving energy efficiency. Many cell-balancing methods rely on converter-based architectures and remain validated only through simulation. This study experimentally validates a previously published adaptive recombination strategy using a prototype with second-life Panasonic NCR18650PF lithium-ion cells. The system employs dynamic series-parallel reconfiguration, relay-based switching, isolated voltage monitoring, and adaptive control to redistribute energy without dedicated balancing converters. Six test cases were evaluated under resting, charging, and discharging conditions using simultaneous and sequential schemes. Complete balancing was achieved in all test cases within the measurement resolution of the prototype. The experiments reproduced the main balancing mechanisms predicted by simulation, particularly under resting and discharging conditions, while also revealing practical deviations under charging operation. These deviations indicate that real current-sharing behavior, cell aging, contact resistance, wiring losses, and measurement constraints can influence recombination performance in ways not fully captured by ideal simulation models. The study therefore provides first-stage hardware evidence for the feasibility of adaptive recombination balancing and identifies key implementation requirements for future real-time, safety-rated, and scalable BMS development. This research contributes to SDG 7 by supporting improved lithium-ion battery utilization and energy efficiency for sustainable electric mobility.