Control & Energy Systems Research Group

1.1 Design and Development of Intelligent Battery Pack for Range Extension of Electric Scooter

Project Code: PSF-CRP/TUBITAK-IV/EV/C-COMSATS (26)

Funding Amount: 19.37 Million PKR

1.1.1 Team Members

• Dr. Ali Arshad Uppal (PI, Pakistan)
• Dr. Qadeer Ahmed (Co-PI, USA)
• Dr. Ahmad Yar (RA)
• Mr. Afaq Ahmed (RA)
• Mr. Sohail Ahmad (RA)
• Mr. Azmatullah (PhD Student)
• Ms. Sheharbano (PhD Student)

1.1.2 Background

The EV market is steadily growing, with projections indicating over 672 million EVs by 2050. Lithium-ion battery packs form the core of EVs.

Cell imbalance may cause premature battery pack shutdown due to the weakest cell. Active Cell Balancing (ACB) redistributes energy to improve safety and range.

1.1.3 Proposed Research

• Selection of an appropriate Active Cell Balancing Network (ACBN)
• Mathematical modeling of SoC, thermal dynamics, and terminal voltage
• High-fidelity modeling of balancing currents and power losses
• Design of range-aware Nonlinear Model Predictive Control (NMPC)
• Simulation-based performance evaluation
• Prototype development for real-time implementation

1.1.4 Intellectual Merit

• Power-loss-aware modeling of ACB networks
• Unified cell modeling for local and global optimization
• Range-extension-aware NMPC design

1.1.5 Broader Impact

• Improved EV safety and reliability
• Reduced emissions and battery degradation
• Enhanced driving range and affordability

1.1.6 Research Contributions

1. Model-Based Quantitative Analysis of a Capacitive Cell Balancing Technique using State-of-Charge (SoC) Estimator
2. Power Losses Aware Nonlinear Model Predictive Control Design for Active Cell Balancing
3. Nonlinear Model Predictive Control Design for Active Cell Balancing and Thermal Management
4. Model-Based Quantitative Analysis of Power Losses Aware Active Cell Balancing Networks with Load
5. Performance Analysis of Model Predictive Controllers for Active Cell Balancing of Electric Vehicle Battery Packs
6. NMPC-Based Performance Evaluation of Active Balancing Networks of Lithium-Ion Batteries for Overnight EV Charging
7. Design and Evaluation of Nonlinear Model Predictive Control for Active Load Balancing in Adjacent Battery Cells
8. Scalable and Modular Control Framework for Managing Active Cell Balancing Challenges in Battery Packs

2.1 Optimal Control of Active Cell Balancing Network for Lithium-ion Battery Pack

Funding Amount: 0.4 Million PKR

• Dr. Ali Arshad Uppal (PI)
• Dr. Syed Bilal Javed (Co-PI, NESCOM)
• Dr. Rizwan Azam (Co-PI, COMSATS)

2.2 Machine Learning Based Control-Oriented Modeling of Underground Coal Gasification

• Dr. Ali Arshad Uppal (PI)
• Mr. Afaq Ahmed
• Dr. Syed Bilal Javed

2.2.2 Research Contributions

1. Nonlinear-Control-Oriented Modeling of the MultiVariable Underground Coal Gasification Process for UCG Project Thar: A Machine Learning Perspective
2. State-Dependent Kalman Filter Design for Nonlinear Dynamic Modeling of Underground Coal Gasification Process
3. CAVLAB Simulator for Underground Coal Gasification (UCG) Energy Conversion Process