EV Battery Electrical & Thermal Simulations
This course focuses on electrical and thermal simulation models of EV batteries. It gives emphasis on the thermal effects which can lead to battery degradation. Also, well designed cooling enables rapid-charging. Next, the course gives the tools for identification of cell properties. Conclusions and lessons learned from customer projects and are shown to give the participants guidelines for optimal thermal design of battery packs.
Who should attend?
This course is intended for electrical engineers who need to learn guidelines for thermal modelling of batteries or for mechanical engineers who need to learn basics of electrical modelling of batteries. Battery experts can appreciate the course for the knowledge and skills in battery simulation.
The objective of the course is to give the participants a quick, yet detailed start into battery simulation. Electrical and thermal simulation models of the batteries will be illustrated by automotive examples: dynamic driving and rapid-charging. The objective is to give the participants tools and skills to develop and apply the basic calculation models on their own. Where possible, course examples will be shared with participants as Excel spreadsheets or MATLAB® scripts.
Basic models of battery cells Equivalent circuit models Heat generation Typical loads Dynamic driving Rapid charging Procedures for lab identification of electrical and thermal properties of cells Guidelines for thermal design of battery packs Cooling methods: passive, active: air or liquid, immersion cooling Cold-plate cooling – calculation models; optimization of heat transfer and pressure drops Lessons learned from customer projects: impact of the mass flowrate, thermal pads, shape of cooling channels and cold-plates on cooling Two perspectives on battery simulation Detailed 3-D simulations Whole-vehicle simulation of the e-powertrain
Dr. Bartosz Górecki
Dr. Bartosz Górecki is the founder and CEO of QuickerSim. He has graduated in Mechanical Engineering from Warsaw University of Technology, studied Computational Engineering Science at RWTH Aachen, received his PhD in Computational Fluid Dynamics. He attended HPC courses at supercomputing centres in Stuttgart, Munich and Bologna. In 2015 he founded QuickerSim – a company that develops Q-Bat – designed for 3-D accurate thermal simulation of automotive battery packs.
All prices are exclusive of VAT.