Phase-asymmetric electric-vehicle (EV) charging can aggravate voltage unbalance in radial distribution feeders, while a smart-inverter battery energy storage system (BESS) can provide both energy shifting and fast reactive-power support. This study designs and evaluates a proximal policy optimization (PPO)-based controller for coordinated active- and reactive-power dispatch under asymmetric EV demand. The analysis uses a corrected phase-decoupled three-phase extension of the IEEE 33-bus feeder, with voltage unbalance quantified using the negative-to-positive sequence voltage ratio. Active-power-only (P-only) and coordinated P–Q controllers are evaluated using identical BESS hardware, operating limits, and terminal state-of-charge (SOC) requirements, enabling the incremental contribution of inverter reactive-power capability to be assessed under matched conditions. Across three independent training seeds, P–Q control reduces daily feeder loss from 3874.822 to 3809.751 kWh/day, worst voltage-unbalance factor (VUF) from 2.7879% to 2.5940%, and mean hourly maximum VUF from 1.5422% to 1.3628%, corresponding to reductions of 1.679%, 6.954%, and 11.632%, respectively, relative to the no-BESS case. The corresponding P-only reductions are 0.610%, 4.362%, and 8.427%, respectively. All reported learned-policy evaluations return the BESS to 50% terminal SOC, preventing the comparison from being biased by net battery depletion. Without retraining, the P–Q policies retain approximately 5.66–7.86% mean worst-VUF reduction under the tested load, photovoltaic, EV-demand, and combined-profile perturbations. The results demonstrate repeatable voltage-unbalance mitigation and show that coordinated P–Q operation provides an incremental benefit beyond active-power-only control under the investigated conditions. However, residual undervoltage under severe loading and the phase-decoupled feeder representation limit the scope of the conclusions.

The aim of this scientific study is to investigate the coupled effects of active battery thermal management on temperature regulation, auxiliary cooling energy demand, and long-term degradation-related exposure under a prescribed tropical heat-soak scenario. A reference 50 Ah equivalent lithium-ion cell is represented by a temperature- and state-of-charge-dependent second-order equivalent-circuit model coupled to a two-node core–surface thermal network. The numerical methods include Coulomb counting, irreversible electrical heat generation, proportional cooling control, time integration of normalized degradation-stress indicators, and ambient-temperature and cooling-setpoint sensitivity analyses. A synthetic 3-day charge–discharge duty cycle and a deterministic 28–42 °C ambient-temperature waveform provide repeatable boundary conditions. Relative to passive operation, the modeled active system lowers peak core temperature while incurring additional cooling electricity demand. The setpoint analysis demonstrates a trade-off between thermal protection, auxiliary energy, and normalized degradation exposure. The framework offers a consistent basis for comparative thermal-management assessment; because the reference parameters and exposure relationships are not experimentally calibrated, it does not establish cell-specific capacity fade, service life, or predictive accuracy.

High ambient temperature and repeated heat-soak exposure can increase the thermal-management burden of electric-vehicle batteries and accelerate temperature-sensitive degradation mechanisms. This study develops a coupled simulation framework combining a second-order resistor–capacitor equivalent-circuit model, state-of-charge dynamics, Bernardi-type heat generation, a two-node core–surface thermal network, proportional active battery thermal management, and Arrhenius-weighted degradation exposure. A repeatable tropical boundary condition of 28–42 \( ^{\circ}C \) is imposed together with a synthetic driving/charging duty cycle. Under the reference parameter set, active thermal management limits the peak simulated core temperature to 35.86 \( ^{\circ}C \) compared with 44.62 \( ^{\circ}C \) for passive operation, a reduction of 8.76 \( ^{\circ}C \). The three-day equivalent-cell BTMS electrical demand is 0.166 kWh and the integrated heat removal is 0.243 kWh. Active cooling reduces the normalized cumulative degradation exposure by approximately 14.0% relative to passive operation. Setpoint sweeps from 28 to 36 \( ^{\circ}C \) quantify the trade-off between cooling energy and degradation exposure. Because cell-specific aging data are not yet available, long-term results are reported as normalized degradation exposure rather than experimentally validated percentage SoH. The framework therefore provides a reproducible basis for subsequent parameter identification, experimental validation, and pack-level lifetime optimization under tropical operating conditions.

Phase-asymmetric electric vehicle (EV) charging can aggravate voltage unbalance in radial distribution feeders, while a smart-inverter battery energy storage system (BESS) can provide both energy shifting and fast reactive-power support. This study designs and evaluates a proximal policy optimization (PPO)-based controller for coordinated active- and reactive-power dispatch under asymmetric EV demand. The analysis uses a corrected phase-decoupled three-phase extension of the IEEE 33-bus feeder, with voltage unbalance quantified using the negative-to-positive sequence voltage ratio. Active-power-only (P-only) and coordinated P–Q controllers are evaluated using identical BESS hardware, operating limits, and terminal state-of-charge (SOC) requirements, enabling the incremental contribution of inverter reactive-power capability to be assessed under matched conditions. Across three independent training seeds, P–Q control reduces daily feeder loss from 3874.822 to 3809.751 kWh/day, worst voltage unbalance factor (VUF) from 2.7879% to 2.5940%, and mean hourly maximum VUF from 1.5422% to 1.3628%, corresponding to reductions of 1.679%, 6.954%, and 11.632%, respectively, relative to the no-BESS case. The corresponding P-only reductions are 0.610%, 4.362%, and 8.427%, respectively. All reported learned-policy evaluations return the BESS to 50% terminal SOC, preventing the comparison from being biased by net battery depletion. Without retraining, the P–Q policies retain approximately 5.66–7.86% mean worst-VUF reduction under the tested load, photovoltaic, EV demand, and combined-profile perturbations. The results demonstrate repeatable voltage unbalance mitigation and show that coordinated P–Q operation provides an incremental benefit beyond active-power-only control under the investigated conditions. However, residual undervoltage under severe loading and the phase-decoupled feeder representation limit the scope of the conclusions.