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Steven Wilkins

Publications and source records attributed to Steven Wilkins.

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Degradation-Aware Fast-Charging of Li-Ion Batteries Using Joint Electrical and Thermal Model Predictive Control

Fast-charging of lithium-ion batteries is essential for electric vehicle adoption, but aggressive charging can accelerate its degradation and create safety risks. This study investigates a control framework that coordinates charging current with active thermal management to minimise charging time, while respecting constraints on electrochemical degradation and thermal safety. A single particle model with electrolyte dynamics (SPMe), extended with a two-node thermal model, represents the battery dynamics and enables the prediction of internal states - used in the control strategy - including anode potential, core temperature, and cell voltage. Two multi-input multi-output control strategies are developed and compared: a classical approach using parallel proportional-integral-derivative (PID) controllers and an advanced model predictive control (MPC) with dual resolution prediction. Both controllers regulate the charging current and thermal resistance to minimise charging time while keeping within the limits of anode potential, core temperature, and cell voltage. The results demonstrate that coordinated thermal-electrochemical optimal control outperforms conventional approaches, achieving a 42.2% reduction in charging time compared to the manufacturer's charging recommendation, without increasing degradation. MPC reduces the charging time by 5.2% compared to PID control, but at a significant computational cost. This improvement demonstrates the untapped potential of integrated thermal management in fast-charging protocols.

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Health-Aware Fast Charging Using Homogenized Model with Heterogeneous Internal State Reconstruction

Fast charging of lithium-ion batteries is limited by lithium plating, which occurs when the anode potential drops below 0 V vs Li/Li+. Model-based control aims to maximize charging current while maintaining anode potentials above this threshold. In this work, a plating-free fast charging strategy is demonstrated using a Homogenized Model (HM) coupled with a classical PID controller. The HM, derived from homogenization theory applied to the Poisson-Nernst-Planck equations, retains the physics of the Doyle-Fuller-Newman model while capturing electrode microstructural heterogeneity in a one-dimensional double-continua formulation. By reconstructing three-dimensional distributions of electrochemical variables from precomputed closure variables, the HM enables non-invasive estimation of heterogeneous anode potentials, acting as a virtual sensor. Through MATLAB-COMSOL co-simulation, a PID controller regulates current to maintain the full 3D anode potential distribution above the plating limit, achieving model-based fast charging at a fraction of the computational cost of high-fidelity models. The results demonstrate the potential of HM-based control for safe, degradation-aware, and efficient fast charging of lithium-ion batteries.

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Multi-objective Optimal Trade-off Between V2G Activities and Battery Degradation in Electric Mobility-as-a-Service Systems

This paper presents optimization models for electric Mobility-as-a-Service systems, whereby electric vehicles not only provide on-demand mobility, but also perform charging and Vehicle-to-Grid (V2G) operations to enhance the fleet operator profitability. Specifically, we formulate the optimal fleet operation problem as a mixed-integer linear program, with the objective combining of operational costs and revenues generated from servicing requests and grid electricity sales. Our cost function explicitly captures battery price and degradation, reflecting their impact on the fleet total cost of ownership due to additional charging and discharging activities. Simulation results for Eindhoven, The Netherlands, show that integrating V2G activities does not compromise the number of travel requests being served. Moreover, we emphasize the significance of accounting for battery degradation, as the costs associated with it can potentially outweigh the revenues stemming from V2G operations.

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