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Ansys & Porsche Motorsport

Electrifying Vehicle Performance

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Pushing New Limits

Together, Ansys and Porsche Motorsport are leading the field in the race to next-generation e-mobility. As Porsche's Official Simulation Partner of the TAG Heuer Porsche Formula E Team, Ansys is powering the design of the automaker’s first-ever, fully electric race car — the Porsche 99X Electric.

This exciting partnership pairs our industry-leading engineering simulation with Porsche’s high-performance automotive engineering, in the development of the Porsche E-Performance Powertrain. Our electrification solutions support Porsche Motorsport’s mission to maximize powertrain efficiency in its electric race cars — and passenger electric vehicles. 

Powering Leading-edge E-mobility

Powering Leading-edge

From maximizing electromagnetic torque and power density to rapidly predicting the power converter and battery temperatures to maximizing overall efficiency of the electric powertrain, Porsche engineers leveraged Ansys’ system-level Multiphysics tools to design the winning formula for the 99X Electric.

These technologies helped Porsche engineers decrease the need to build physical prototypes, enabling virtual testing of design concepts to quickly arrive at an optimum design. This delivered significant energy efficiency for vital 99X Electric subsystems and components, equipping the car to maintain tremendous speeds over extended distances on the track.

Connecting to Simulation

The overall performance of the electric powertrain is directly affected by the efficiency and power/torque density of the electric machine. For this reason, permanent magnet synchronous machines (PMSM) are typically chosen for the battery electric vehicles. The performance of the electric machine should be optimized for the whole range of the speed/torque load points over racing track, considering the high-frequency ripples in the stator currents due to inverter switching and temperature effects.

All fully electric race cars in an ABB FIA Formula E World Championship use the same main traction battery pack throughout the season. The available energy in an ABB Formula E race is limited; thus, it is essential to have accurate models for the battery electrical and thermal behavior to predict the battery state of charge, voltage, and temperature based on the power profile of a specific racetrack. This is achieved by coupling an Equivalent Circuit Model (ECM) of the electrical behavior with a Dynamic Reduced Order Model (Dyna-ROM) of the thermal behavior of the battery.

When electric machine generated power transduces in torque at the wheels, the reduction gear system plays a critical role. The design challenge for engineers is to maintain high the efficiency and modulation of the electric driveline, while keeping under control thermal dissipation and noise harshness of the organs during the entire drive cycle. Ansys Multi-domain simulation is the key tool for the design of optimal and efficient transmission drivelines.

The optimal design of traction inverter for electrical vehicles is crucial for the overall performance of electric powertrain. High power density, high voltage and current ratings together with fast switching speeds of new wide bandgap semiconductor power devices set challenges to the design of traction inverter. Efficiency optimization of traction inverter requires accurate estimation of power losses under different operating conditions, such as switched current and voltage levels and temperature, which change during the race. Optimizing the performance as well as ensuring functional safety and reliability as keystones for a successful race.

As the overall efficiency of the electric powertrain is typically more than 90%, further optimization is challenging. Especially in high-performance electric vehicles, the efficiency over one or multiple laps on a racing track is crucial. It requires accurate estimation of power losses in each component of the powertrain and the analysis of the interaction between components under different operating conditions, such as temperature, speed/torque load point and battery state of charge (SOC). Thus, optimizing component efficiency is not equivalent to optimizing overall efficiency of the powertrain. System simulation using reduced order modeling (ROM) techniques and integrating realistic control enables performance optimization of the electric powertrain.