Mohammad Khan

Model-based design, rapid control prototyping, HMI engineering, simulation-based validation and CI/CD workflows for hybrid power systems. Client work includes fuel-cell and electric-hybrid vehicle benchmarking, powertrain and thermal-system analysis, data quality and reporting, customer presentations, and engineering process improvement.

Designed and optimized hybrid systems for renewable-energy power plants, focusing on balance-of-system design. Assessed electrical-network equipment and managed battery R&D laboratory operations. Contributed to BESS standards, technical requirements, sizing, O&M, warranty feedback and quality-cost analysis.

Managed complex energy storage projects involving multiple stakeholders. Oversaw contract and procurement activities, technical specifications and certifications, and regulatory compliance documentation for electrical substations. Supported EPC bidder review, RFPs, technical due diligence, utility-scale ESS sizing and value engineering.

Designed model-driven development and verification solutions for safety-critical embedded systems for advanced battery management systems, combining ISO 26262, HIL verification and quality assurance.

PhD research on thermal management of battery systems in electric-vehicle and smart-grid applications. Characterized electrical, thermal and electrochemical battery behavior; built a thermal-cell experiment platform; developed multiphysics models from calorimetric measurements; and studied techno-economic battery sizing and state-of-charge estimation.

Integrated battery systems with the grid and developed online state-of-charge estimation using nonlinear optimization, including genetic algorithms and Levenberg–Marquardt. Performed battery-cell characterization, modelling and regression testing.

Doctoral thesis: Thermal Management of Battery Systems in Electric Vehicle and Smart Grid Application. Research covered battery electrical and thermal characterization, calorimetry, multiphysics thermal modelling, state-of-charge estimation and techno-economic optimization.