Nabin Regmi

•Evaluated system architectures to select optimal alternatives meeting stakeholder and system requirements. •Contributed to the development and management of system requirements based on stakeholder inputs, maintaining bidirectional traceability in Polarion. •Defined DVPR test plans, designed test setups, and analyzed test result data for high-voltage battery pack validation. •Created system-level schematics and boundary diagrams for high-voltage battery packs. •Led development of system-level DFMEA, integrating it with requirements and verification plans. •Reduced overall pack cost through structured VA/VE activities. •Led post-test teardown activities of battery packs and investigated root causes of failures. •Mentored junior engineers and interns on battery system testing, design integration, and pack teardown.

•Investigated thermal runaway propagation (TRP) events in packs and modules; identified multiple TRP mitigation techniques and early-detection signals through literature review and state-of-the-art technology exploration. •Led development of a Thermal Runaway Warning Signal Algorithm enabling early detection of thermal runaway signs and real-time warnings, supporting compliance with ECE R100 safety requirements. •Analyzed test data, defined signal thresholds, and collaborated with software and electrical teams to validate and implement the algorithm in production battery packs. •Directed cross-functional teams in integrating the TRP algorithm into battery packs, achieving a >15-minute detection-to-hazardous-event interval across all TRP-tested packs. •Led development and integration of a custom gas sensor for thermal runaway detection, collaborating with supplier and purchasing teams to overcome the absence of commercially available solutions. •Conducted extensive sensor testing across supply voltage ranges, temperatures, torque, and pressure conditions, ensuring successful calibration and system integration. •Performed system-level modeling of high-voltage battery packs and simulated pack behavior across various mission profiles and BMS settings.

·Developed a battery EV simulation tool that includes a detailed model of an electric vehicle (Driver, Primary Controller, EV Powertrain with High Voltage Battery Pack, and Vehicle Dynamics) including the BMS calibrated through experimental data. ·Calculated power limits for SonyVTC6 cell using HPPC, RC-ID and V-I-SOC based methods. ·Determined how aging is affecting the update of power limits for HPPC, RC-ID, and V-I-SOC-based methods. ·Applied different power limits to the vehicle model and showed the impact on the performance of the vehicle. ·Simulated the tool on various mission profiles and BMS settings to unveil the benefits and limitations of map-based power limit estimations. ·Compared the vehicle parameters like vehicle speed, and friction brake ratio to understand the effect on vehicle performance. ·Analyzed metrics like battery voltage, current, and SOC with and without integration of power limits inside the battery pack. ·Compared the results with the simulated aged battery pack.

·Development of a Modelling, Simulation and Analysis (MS&A) tool for emerging UAM battery pack technologies considering mission and vehicle specifications. ·Upgraded the tool by adding new chemistries (Panasonic NCR18650 [NCA] and Toshiba SCiB [LTO]). ·Performed electrical and thermal modelling of the additional chemistries. ·Collected aging parameters data for NCA/LTO chemistries cells from the available literature and applied those parameters to perform the aging model of the cell.

Coursework focused on lithium-ion batteries and electric vehicle battery systems and associated powertrain architecture (both hybrid and all-electric vehicles). Coursework: ME7383-Electrochemical Energy Storage Systems for Automotive Applications. ME8322-Vehicle System Dynamics and Control. ME7384-Energy Optimization and Control of Advanced Vehicles. ME7236-Powertrain Dynamics. ME5372-Design and Control of Mechatronic Systems. ME5775-Applied Machine Learning for MAE. CS5052-Artificial Intelligence ECE5463-Introduction to Real-Time Robotics. ME5168-Introduction to Finite Element Method.