Multiple original equipment manufacturers (OEMs) and startups are investing time and resources into mastering the shift from manual, mechanical platforms to autonomous, electric vehicles (EVs). Companies that can turn the combination of EV performance, range, and durability into commercial success will increasingly dominate the competition.

This complexity would be impossible to master without advanced simulation processes in place to drive the sizing, shape, and performance tradeoffs that result in a successful EV product. While computer simulation has been used by conventional automakers for some time, the latest methodologies available now are a perfect match for EV design.

New vehicle types

EVs are truly new products, with many different configurations, components, and accompanying physics to consider during conceptualization and design. For example, the performance of the huge battery packs must be optimized – a Tesla Model 3 requires 4,416, 2.8" battery cells, according to an April 2019 article in Bloomberg Businessweek. This involves maintenance of a narrow temperature gradient, impact protection, and aging predictions. The vehicle’s heating, ventilation, and air conditioning (HVAC) and overall thermal behavior must be tightly controlled, without undue burden on the battery charge. And the related power electronics of the vehicle must balance DC/DC dual tension, withstand mechanical and thermal stress, and maintain power and signal integrity through electrical ripples.

Furthermore, the electric drive system powered by the battery is completely different from a traditional internal combustion engine (ICE). Lubrication, thermal management, strength and stiffness, durability, and electromagnetic (EM) performance are unique to EVs, as are noise, vibration, and harshness (NVH) requirements.

A typical electric motor has 50 parts compared to 1,200 in an ICE, but the structural and EM interrelationships between rotor, stator, housing, and gears introduce complexities not seen in any combustion vehicle. Lightweighting is important in all vehicles, but EV architecture and body designs take lightweighting as far as possible, offering new configuration and packaging opportunities for modularization.

Simulation solutions

Integrated multiphysics simulation has advanced to the point where the key characteristics of EVs – particularly those unique to EM, NVH, and multi-body dynamics – can now be addressed. Simulation can evaluate the function of the electric drive and EM effects on stator, rotor, and antenna placement (critical for autonomous EVs). Battery range can be predicted by simulating thousands of miles in every driving condition, using one-dimensional models coupled with multibody simulation and advanced computational fluid dynamics (CFD). Battery safety and durability can be assessed against attendant thermal, structural, electrical, and chemical concerns.

Sound radiation and pressure from the drivetrain, and irritating NVH issues can be more noticeable in quieter EVs than in noisier ICE vehicles, and those overall acoustic factors can now be explored in-depth through advanced simulation.

Managing challenges

Most EV producers begin a new vehicle concept with a systems-engineering approach based on fast, one-dimensional, equation-driven models. This allows quick execution of performance and tradeoff studies to understand the interrelationships between different motor sizes, power electronics, gear ratios, and battery requirements.

Next, designers create CAD geometry models of vehicle components based on the performance parameters driven by the system model, with trade-offs based on cost and packaging requirements. If system requirements change, each CAD model may need to be updated to reflect packaging and performance changes.

Finally, engineers perform multiphysics simulations on the model to study NVH, fatigue, thermal management, and EM interference. Problems are identified early in this kind of virtual environment, well ahead of real-world prototyping. Identifying issues leads to design changes and validation. Changes then pass back to the CAD and then the system model. The process repeats until the entire desired EV configuration is optimized for production.

If the design team is working on a unified commercial software platform, all this happens automatically: CAD model parameters are tied to and driven by the system model. Any updates from system requirements to simulation results and back again happen automatically and are communicated to the project’s team. Everyone adheres to a single source of truth so they can fully understand the consequences of various tradeoffs before finalizing detailed design and starting with prototypes.

Simulation of an electric drive system with flex-body components.

Expert advice

A professional consulting organization can help align a company’s existing engineering tools and processes to work together, connecting multi-CAD, simulation tools, and data into a single connected environment. The consulting team can recommend methodologies and create a validation and simulation process optimized for the challenges they are trying to solve. While a single integrated environment may be the most efficient way to integrate communication and data management, many companies already have investments in multiple toolsets that they may not want to lose. In this situation, consultants can help understand where certain tools are most valuable and what choice-based tradeoffs exist.

Ideally, a company should consult with an outside expert at the earliest stage of EV concept development. Going onto a commercial platform at that point offers time-to-market advantages that can be huge in the fast-paced EV race. But it can be equally valuable to seek counsel at any stage in the process to identify the clearest route forward to optimum EV design.

Adaptive Corp. https://www.adaptivecorp.com

About the author: Adaptive Corp. Chief Operating Officer Wayne Tanner is responsible for sales and services for PLM, additive manufacturing, simulation, and metrology business lines. He can be reached at wtanner@adaptivecorp.com.