1. Current Research
1.1. Design and Development of Intelligent Battery Pack for Range Extension of Electric Scooter (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 Ahmed (RA), Mr. Azmatullah (PhD student) and Ms. Sheharbano (PhD student)
1.1.2. Background
The electric vehicle (EV) market is steadily growing, with projections indicating over 672 million EVs on the roads by 2050. The battery pack, primarily lithium-ion, serves as the core of an EV, influencing its range. Cell imbalance, a key factor limiting EV range, can lead to battery pack shutdown based on a single cell’s condition. Active cell balancing (ACB) emerges as a crucial solution to counter cell imbalance, enhancing overall battery pack performance, safety, and consequently, EV range.
1.1.3. Proposed Research
EV battery packs are equipped with a battery management system (BMS), responsible for monitoring and control. The cell equalization circuit, a pivotal BMS component, plays a vital role. This research aims to extend EV range through state-of-charge (SoC)-based ACB, with objectives including:
- Selecting an appropriate ACB network (ACBN)
- Developing a mathematical model for a cell, considering SoC, thermal dynamics, and terminal voltage
- Detailed mathematical modeling of ACBN, encompassing cell dynamics, balancing currents, and power losses
- Designing a range-maximizing, robust nonlinear model predictive control (NMPC) using the ACBN model
- Conducting a simulation study to showcase NMPC performance and EV range extension
- Developing a prototype for real-time implementation.
1.1.4. Intellectual Merit
Despite extensive research in ACB control, certain avenues require exploration. Research gaps include:
- Often overlooked high-fidelity modeling of balancing currents and power losses, crucial for assessing ACBN efficiency
- The subjective choice of a cell dynamics model, necessitating alignment with both ACB (local) and EV range extension (global) paradigms
- The nascent stage of research on range extension-aware NMPC, demanding further development.
1.1.5. Broader Impact
The control system’s design for EV battery packs extends beyond immediate applications, offering broader impacts such as:
- Advancing scientific knowledge by combining data-driven and model-based methods to understand and control battery systems, capturing their complex dynamics.
- Enhancing EV industry innovation and competitiveness through a novel technique optimizing battery performance and safety under diverse conditions.
- Improving environmental and social benefits of EVs by reducing emissions, energy consumption, and battery degradation, while increasing driving range, reliability, and affordability
1.1.6. Research Contributions
- Model-Based Quantitative Analysis of a Capacitive Cell Balancing Technique using SoC Estimator
- Power Losses Aware Nonlinear Model Predictive Control Design for Active Cell Balancing
- Nonlinear Model Predictive Control Design for Active Cell Balancing and Thermal Management
- Performance Analysis of Model Predictive Controllers for Active Cell Balancing of Electric Vehicle Battery
- NMPC-Based Performance Evaluation of Active Balancing Networks of Li-ion Batteries for Overnight EV Charging
- Design and Evaluation of Nonlinear MPC for Active Load Balancing in Adjacent Battery Cells
- Scalable and Modular Control Framework for Managing Active Cell Balancing Challenges
2. Completed Projects
2.1. Optimal Control of Active Cell Balancing Network for Lithium-ion Battery Pack–Funding amount: 0.4 Million PKR
2.1.1 Team Members
Dr. Ali Arshad Uppal (PI), Dr. Syed Bilal Javed (Co-PI, NESCOM) and Dr. Rizwan Azam (Co-PI, COMSATS)
2.2. Machine Learning Based Control-Oriented Modeling of Underground Coal Gaisfication (UCG) Process
2.2.1 Team Members
Dr. Ali Arshad Uppal (PI), Mr. Afaq Ahmed and Dr. Syed Bilal Javed