Changfu Zou
I am a Professor and PI of the Energy Systems and Optimal Control (eSOC) group at the Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden. I received my PhD from the University of Melbourne, Australia, and was a visiting student researcher at the University of California, Berkeley, USA. I joined Chalmers as a Researcher in 2017, became an Assistant Professor in early 2019, an Associate Professor in early 2022, and a tenured Associate Professor later in 2022, all within the same department. My research focuses on advanced modelling and automatic control of energy storage systems, particularly lithium-ion batteries. Much of my work is conducted in close collaboration with industry partners, such as Volvo, Scania, and ABB. As PI or Co-PI, I have received funding from the Swedish Research Council (including both Starting Grant and Project Grant), European Commission, Swedish Energy Agency , Swedish Innovation Agency, Knut and Alice Wallenberg Foundation, and others. I have been a recipient of recognitions, such as the IEEE Vehicular Technology Society (VTS) Best Vehicular Electronics Paper Award, IEEE TTE Prize Paper Award, IEEE VTS Climate Challenge Award, Nordic Energy Challenge Award, and selection to the Royal Swedish Academy of Engineering Sciences (IVA)'s 100 List. I have served as a review expert for research grants by the European Commission (e.g., for Horizon Europe CL5), US National Science Foundation, Academy of Finland, Cariplo Foundation in Italy, Natural Sciences and Engineering Research Council of Canada (NSERC), among others. I currently serve as an associate editor/editorial board member for journals, such as IEEE TVT, IEEE TTE, IEEE T-ITS, and Cell Press journal iScience.
Showing 86 publications
Lifelong Reinforcement Learning for Health-Aware Fast Charging of Lithium-ion Batteries
A fast fixed-point solution framework for the P2D model of lithium-ion batteries
Mathematical Modeling for Reconfigurable Battery Systems With Parallel-Series Connections
Listening to silent signals: Wireless internal sensing redefines battery safety intelligence
A Unified Modeling Framework of Reconfigurable Battery Systems for Optimal Control
Electric-powered air traffic network with integrated aircraft-battery modelling
Smart sensing breaks the accuracy barrier in battery state monitoring
A Unified Model for Active Battery Equalization Systems
Multi-frequency excitation enables one-second battery diagnostics across life cycle chain
Robust Model Predictive Control for Fast Discharging of Retired Lithium-ion Battery Cells
Battery digital twins from the bottom up: Molecular precision at system scale
Learning chemical potentials and parameters from voltage data for multi-phase battery modeling
A review of mechanical abuse safety of lithium-ion batteries under different aging approaches
Model Predictive Cooling Control of Cylindrical Battery Cells Through Tab and Surface Channels
Nonlinear Model Inversion-Based Output Tracking Control for Battery Fast Charging
Hypergraph-Based Unified Model Development for Active Battery Equalization Systems
Life-Cycle analysis of economic and environmental effects for electric bus transit systems
Detecting abnormality of battery lifetime from first-cycle data using few-shot learning
MINN: Learning the dynamics of differential-algebraic equations and application to battery modeling
Early prediction of battery life by learning from both time-series and histogram data
Vehicle-to-grid optimization considering battery aging
Ensemble Nonlinear Model Predictive Control for Residential Solar Battery Energy Management
Analysis of Potential Lifetime Extension Through Dynamic Battery Reconfiguration
Optimization-free fast charging for lithium-ion batteries using model inversion techniques
Practical battery state of health estimation using data-driven multi-model fusion
Combining offline and online machine learning to estimate state of health of lithium-ion batteries
State of Power Prediction for Battery Systems with Parallel-Connected Units
Offline and Online Blended Machine Learning for Lithium-Ion Battery Health State Estimation
Analysis and Estimation of the Maximum Switch Current during Battery System Reconfiguration
Sensitivity Analysis of the Battery System State of Power
Fast Charging Control of Lithium-Ion Batteries: Effects of Input, Model, and Parameter Uncertainties
Control-Oriented Modeling of All-Solid-State Batteries Using Physics-Based Equivalent Circuits
Model Order Reduction Techniques for Physics-Based Lithium-ion Battery Management: A Survey
A PDE Model Simplification Framework for All-Solid-State Batteries
Active Balancing of Lithium-Ion Batteries Using Graph Theory and A-Star Search Algorithm
Electrochemical Model-Based Fast Charging: Physical Constraint-Triggered PI Control
Run-to-Run Control for Active Balancing of Lithium Iron Phosphate Battery Packs
Novel Mesoscale Electrothermal Modeling for Lithium-Ion Batteries
Next-Generation Battery Management Systems: Dynamic Reconfiguration
Cell Balancing Control for Lithium-Ion Battery Packs: A Hierarchical Optimal Approach
Dynamic modeling and coordinate control for an engine-generator set
Predicting battery aging trajectory via a migrated aging model and Bayesian Monte Carlo method
Near-Fastest Battery Balancing by Cell/Module Reconfiguration
Advanced Vehicle State Monitoring: Evaluating Moving Horizon Estimators and Unscented Kalman Filter
Load-responsive model switching estimation for state of charge of lithium-ion batteries
Model-based state of charge estimation algorithms under various current patterns
Model Predictive Control for Lithium-Ion Battery Optimal Charging
Electrochemical estimation and control for lithium-ion battery health-aware fast charging
Random forest regression for online capacity estimation of lithium-ion batteries
Real-time monitoring of capacity loss for vanadium redox flow battery
Charging pattern optimization for lithium-ion batteries with an electrothermal-aging model
A fast estimation algorithm for lithium-ion battery state of health
Technological developments in batteries: A survey of principal roles, types, and management needs
A framework for simplification of PDE-based lithium-ion battery models
Multi-time-scale observer design for state-of-charge and state-of-health of a lithium-ion battery
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Showing 29 research projects
Data-efficient learning for mobile manipulation tasks using multi-modal data
Advanced microscopy of air-sensitive battery materials
Enhancing vehicle battery systems with dynamic configuration for smart energy management
User behaviour informed optimal control for vehicle-home-grid integration
Multiphysics modelling and monitoring of lithium-ion cells for next-generation management
Implantable Graphene Sensor and Its Application to Batteries
E-powertrain predictive maintenance using physics informed learning (TEAMING)
Data-driven lifetime extension and performance optimization for vehicle battery systems
User behaviour informed learning and intelligent control for charging of vehicle battery packs
Modelling plating morphology in lithium-ion batteries for enhanced safety
Electric vehicle energy optimization for improved sustainability
Electrochemical model parameter identification for health-aware battery management
Lithium-ion battery control for faster charging and longer life
Data driven battery aging prediction
Thermal modelling and fault prognosis for Li-ion battery systems
Energy optimisation and control of autonomous electric vehicles
Battery control via adaptive modeling and predictive control
BattVolt - Battery control with dynamic reconfiguration and controllable voltage
Dynamic reconfiguration of vehicle battery systems
Optimal usage of vehicle battery by multi-scale modelling
More efficient and health conscious usage of lithium ion batteries by adaptive modeling