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20212025
most citedLithium-ion Battery Capacity Prediction via Conditional Recurrent Generative Adversarial Network-based Time-Series Regeneration

2 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SY2025

Equivalent-Circuit Thermal Model for Batteries with One-Shot Parameter Identification

Myisha A. Chowdhury, Qiugang Lu

Accurate state of temperature (SOT) estimation for batteries is crucial for regulating their temperature within a desired range to ensure safe operation and optimal performance. Th…

eess.SY2025★ 2 cited

Lithium-ion Battery Capacity Prediction via Conditional Recurrent Generative Adversarial Network-based Time-Series Regeneration

Myisha A. Chowdhury, Gift Modekwe, Qiugang Lu

Accurate capacity prediction is essential for the safe and reliable operation of batteries by anticipating potential failures beforehand. The performance of state-of-the-art capaci…

eess.SY2024

Adaptive Safe Reinforcement Learning-Enabled Optimization of Battery Fast-Charging Protocols

Myisha A. Chowdhury, Saif S. S. Al-Wahaibi, Qiugang Lu

Optimizing charging protocols is critical for reducing battery charging time and decelerating battery degradation in applications such as electric vehicles. Recently, reinforcement…

eess.SY2022

A Novel Entropy-Maximizing TD3-based Reinforcement Learning for Automatic PID Tuning

Myisha A. Chowdhury, Qiugang Lu

Proportional-integral-derivative (PID) controllers have been widely used in the process industry. However, the satisfactory control performance of a PID controller depends strongly…

eess.SY2021★ 2 cited

Stability-Preserving Automatic Tuning of PID Control with Reinforcement Learning

Ayub I. Lakhani, Myisha A. Chowdhury, Qiugang Lu

PID control has been the dominant control strategy in the process industry due to its simplicity in design and effectiveness in controlling a wide range of processes. However, trad…