Daniel Edward is a master’s student in mechanical engineering at McMaster University, with two years of experience at the McMaster Automotive Resource Centre (MARC) and the Canada Excellence Research Chair (CERC) Laureate Program. He currently serves as the Propulsion Controls and Modelling (PCM) Co-Lead for the McMaster Engineering EcoCAR Team. In this role, he contributes to the development, troubleshooting, testing, and validation of propulsion control algorithms for a 2023 Cadillac Lyriq—focusing on enhancing drivability, efficiency, and performance in electrified vehicles.
Full Profile
Daniel Edward is a master’s student in mechanical engineering at McMaster University, specializing in vehicle electrification and intelligent propulsion control systems. With a background in automotive and vehicle engineering technology, he has developed strong expertise in control systems, vehicle dynamics, drivetrain design, and C++ programming. His research focuses on supervisory propulsion control, electrified vehicle modelling, one-pedal driving strategies, and software/hardware-in-the-loop (SIL/HIL) validation.
Daniel’s involvement in advanced automotive research began during his undergraduate studies, when he joined the McMaster Engineering EcoCAR Team as a member of the Propulsion Controls and Modelling (PCM) group. His strong contributions led to a co-op placement with the Canada Excellence Research Chair (CERC) Laureate Program at the McMaster Automotive Resource Centre (MARC), where he later advanced to the role of PCM Co-Lead.
In this leadership position, Daniel has contributed to the development, testing, and implementation of real-time propulsion control features for a 2023 Cadillac Lyriq as part of the EcoCAR EV Challenge. His work includes developing the accelerator pedal map and rate limiter, coordinating high-voltage startup and shutdown sequences, and implementing regenerative braking through brake blending. He is currently leading the design and deployment of a one-pedal driving control algorithm to improve vehicle efficiency and driving performance.
Daniel is proficient in industry-standard tools such as MATLAB/Simulink, Vector CANalyzer, and Microsoft Office. His hands-on experience in data analysis, model-based development, and HIL testing positions him to address the complex, interdisciplinary challenges of modern electric vehicle systems. Through his research and leadership, he is committed to advancing smart, efficient, and sustainable mobility solutions.
