Dr. Vincent LECONTE
Altair Engineering Inc.
Advanced Multiphysics Optimization Techniques For Electric Motor Design
The electrification of vehicles is bringing new challenges for the design of electric machines. Designers need to consider multiphysics constraints for motors to be energy efficient, lightweight, compact, and silent. Electric machines must be efficient throughout a wide range of torques and speeds and needs to be then optimized over full driving cycles. Because they are often operated at high speeds, rotors are also submitted to high mechanical stress. The best compromise between electromagnetic performance, weight and stress is not easy to be found. Torque ripples, vibrations and extra losses are introduced by the use of PWM techniques for control. It means simulations must include the influence of the currents harmonic content. The cooling and thermal analysis is also a key topic in a search for high power densities. New modeling techniques, simulation strategies and design processes are developed to help designers handling this complexity. Parameter based optimization processes can consider multiple physics integrated in single loops, and should also include the influence of the control, to avoid numerous manual iterations. In complement, shape and topology optimizations can be performed to create innovative power dense structures. This presentation will detail examples that use such advanced optimization techniques for the design of traction motors.
Vincent LECONTE is responsible for Altair’s Electrification solution. Before joining Altair, he was CEDRAT’s Chief Technical Officer for 7 years, guiding the evolution of Flux software. Before that, he spent about 10 years with Schneider Electric, first designing innovative electromechanical components, and then being responsible for electromagnetic simulation methods and tools at corporate level. He has a PhD in Electrical Engineering from the Institut Polytechnique de Grenoble, France. He has contributed to more than 60 technical publications in the field of electromagnetic modelling.
Prof. Dr. Surin Khomfoi
An ANN-based technique for Assessing Lithium-Ion Battery Health in Electric Vehicles applied in PEA-VOLTA Platform
This research focuses on studying the estimation of state of health (SoH) for lithium-ion batteries utilizing an Artificial Neural Network (ANN). The proposed technique is a function which is applied in PEA-VOLTA platform providing a service by Provincial Electricity Authority of Thailand (PEA). The primary objective is to examine the correlation between the DC internal resistance and the battery’s SoH. A notable advantage of DC internal resistance measurement is its non-invasive nature, as it does not necessitate battery removal from the system. By analyzing degradation patterns observed during multiple cycles, the relationship between DC internal resistance and battery health is studied and subsequently employed to train the ANN. The developed ANN model is then tested on various battery packs, demonstrating acceptable error. The battery and analyzes parameters obtained from EV charging, including voltage, current, and charging time are also used to validate the propose predictive model. The analysis of experimental results reveals that as the service life of EVs increases, the charge to voltage ratio decreases. This ratio can serve as an indicator of battery health. As a result, this ANN model can serve as a valuable tool in early detection of potential battery failures caused by degradation, enabling timely interventions and maintenance actions.
Surin Khomfoi was born in Thailand. He received his B.Eng. and M.Eng. in Electrical Engineering from the King Mongkut’s Institute of Technology Ladkrabang (KMITL), Bangkok, Thailand, in 1996 and 2000, respectively; and his Ph.D. degree in Electrical Engineering at the University of Tennessee, Knoxville, TN, USA, in 2007. Since December 1997, he has been a lecturer with the Department of Electrical Engineering, KMITL, where he is currently a professor. His current research interests include multilevel power converters, renewable energy applications, fault diagnosis, electric vehicle infrastructure and smartgrids. Dr. Khomfoi is a Member of the Eta Kappa Nu Honor Society and a Senior Member of the IEEE. He was a recipient of academic scholarship awards, including full academic scholarship for his B.Eng., M.Eng., and Ph.D. studies from the Energy Policy and Planning Office (EPPO), Ministry of Energy Thailand.