Simulation Driving Innovation in E-Propulsion

The seminar will include keynote speeches, interactive live interviews, technical presentations and live demonstrations, with sessions on gears, electric-motors, battery & fuel cells, and systems simulation.

In this presentation, Jamie Buchanan will show the evolution of simulation and introduce the importance of multi-physics optimisation with respect to the complex mechatronic systems Altair’s customers are delivering.  He will highlight some of the key technologies and processes that Altair offers which will be covered in further detail by some of the presenters in talks through the day.

Ian Constance will look at the key trends disrupting the automotive sector and the need to innovate faster, with greater levels of productivity and lower costs in order to thrive in an era of unprecedented change.

A no nonsense presentation of the current opportunities for growth in demand for hydrogen technologies in the UK on the back of national, regional and local interest in the role they will play in delivering net-zero. Let’s think synergies rather than competition with other zero-emission solutions and be aware of all the applications that need to be decarbonized not just passenger cars, or even road transport.

In close cooperation, ZF and Altair have developed a unique environment based on Altair e-Motor Director to support the synthesis of complete e-motor platforms. From previously calculated design of experiments (DoEs) and given requirements, an attempt is made to find a platform that meets all requirements and at the same time keeps costs low by using identical parts that can be reused in the individual e-motors. In principle, it would be possible to build each e motor from as many identical parts as possible, which would lead to a low- cost platform, but the requirements cannot be optimally met.

It would also be possible to optimize all e-motors only to the requirements, regardless of identical parts. That would lead to the optimum in terms of meeting the requirements but would not be a good solution in terms of costs, since all the parts for an e-motor must be specially manufactured. The aim of this developed environment is to find the optimum between these two extremes by counting the number of identical parts and also weighting them depending on the costs. The finally found e-motor platform now represents the trade-off in terms of meeting the requirements while at the same time increasing the number of identical parts and thus reducing costs.

The Alstom Ornans site develops electric tractions motors for railway applications. Several high voltage architectures (750V to 25kV) are designed: metro, tramway, regional train, locomotive and high-speed train for a multitude of customers worldwide. The future designs have a lot of challenges to face: cost reduction, volume reduction, rotational speed increase, long lifetime, stronger standards… In addition, the electric motors are complex to design because of a plurality of physics: electrotechnics, mechanical, thermal and acoustic. So, to fulfill all requirements, multiphysics optimizations need be performed. Alstom has evaluated several options to run coupled optimization. The goal of the “Grand challenge” is to run electrotechnical optimization coupled with mechanical optimization on internal permanent magnet rotors. The presentation will show how Altair Simlab will be used to link several software to setup multiphysics calculations. Altair Hyperstudy will be used to drive Simlab for parametric models and manage the coupled optimization.

Tony Harper is Director at the Faraday Battery Challenge working closely on a number of large, strategic projects on Electrification and Autonomy with Innovate UK. He was previously Director of Research Engineering for Jaguar Land Rover. Tony is a Fellow of The Royal Academy of Engineering and an elected member of the UK Automotive Council Technology Group.

Intelligent Energy are developing new hydrogen fuel cell products for automotive, stationary and heavy duty on/off highway for a future of reduced carbon emission, with a production pathway to gigafactory capability. CAE methods are being applied increasingly to the product development process, with multi-phase CFD, implicit and explicit FEA models, together with recent application of multi-physics in-cell modelling. This presentation provides an overview of the application space and products deployed by Intelligent Energy, with selected samples of applied CAE to the detailed product development work.

The ever increasing demand for renewable energy worldwide means that developing efficient energy storage techniques are of critical importance. Materials in particulate forms are commonly used in essential energy storage systems, e.g. lithium-ion battery electrodes. In this project, Discrete Element Method (DEM) simulation is used to investigate the calendering process of lithium-ion battery electrodes. By combining DEM, X-ray computed tomography and electrochemical analysis, electrode mechanical and structural properties were investigated. Detailed stress and structural evolutions at microscopic particle scale were analysed. This work provides a highly promising method to quantitatively predict lithium-ion battery electrode performance, and presents a digital tool for the next generation battery electrode manufacturing.

The use of Axial Flux Machines (AFM’s) in EV applications presents a number of challenges both in the design process as well as in volume production. Soft Magnetic Composite (SMC) materials are applied as an alternative to electrical steel laminations and promise to introduce design freedom whilst simultaneously address concerns related to production. In order to consider such machines in the early concepting phase of development, a simplified rapid modelling approach in Altair Flux is used to characterise a machine. The characterised machine including loss and performance estimations is then exported and applied in the electrified Powertrain Optimisation Process (ePOP) simulation environment, which allows a system level assessment of various powertrain candidates. A comparison of an Axial Flux Machine (using SMC) and a conventional PM radial flux machine in the same target EV application is presented.

This presentation will discuss a collaboration between electric bus manufacturer, Switch Mobility, and Altair, to accurately predict the range of electric vehicles through the development and deployment of a digital twin. With accurate range prediction, Switch Mobility can give its public transport authority customer confidence that electric buses can meet the requirements of their bus routes and be a viable alternative to traditional ICE vehicles.

Simulation is now the dominant technology driving the design process. Optimization and machine learning, together with the availability of inexpensive computing place simulation at the heart of the design process, and at the evolution of the Digital Twin. EV battery packs present a unique opportunity to showcase the power of simulation and the benefits of the Digital Twin.

Battery Thermal Management Systems (BTMS) use logic to control the thermal balance needed for reliable and long-lasting battery pack designs. A key driver is ensuring cells operate under load within a specified temperature window. The system design challenge is to balance the heat generated by current demand and supply against an efficient cooling strategy.

A Digital Twin has been created which presents a virtual representation of a physical battery pack subject to a transient duty cycle. The Digital Twin mimics the embedded control logic of the hardware to manage system heating and cooling during the event.

Capturing the complex physics and system response with the Digital Twin in timescales commensurate with the physical hardware enhances the role of simulation within the UK battery development community. The battery Digital Twin presents new opportunities for rapid, holistic, design exploration and innovation.