Electric Motor Optimization

Because of the rising complexity in new vehicles technologies, model-based design & systems engineering is needed to cascade the requirements and trace back any modification along the engineering lifecycle.

Find out more in this presentation of a customer case about electric motor optimization:

Electric motor optimization Scilab

This presentation was performed at the ESI Forum in Japan last month (november 2019).

 

Every single car goes through model-based design

Traditional car makers are facing organizational challenges when designing a new electric vehicle. The basic functions of the vehicle are deeply impacted by the changes in terms of technology. In the first place the powertrain, switching from internal combustion engine and fuel tanks to electric motor and battery. But also chassis, body and interior because of the many interactions between the main automotive sub-systems. Basically, there is a need to go back to the functional requirements to provide a new implementation answering the electrification challenge.

This is exactly what model-based design & systems engineering provides as a framework:

  • Starting with requirements at the vehicle level
  • Propagate the technical specifications at the component levels (motor, batteries,...)
  • Verify & validate the implementation through simulation & tests

 

Powertrain: new design trade-offs

The great thing about a combustion engine is its large range of work. It can deliver power at various engine speed, making it suitable for a large amount of applications (mobility being one of the strongest).

However combustion engines are physically limited to no more than 50% of efficiency as a result of the laws of thermodynamics(most of the heat is not turned into mechanical energy). An electric motor on the other end typically provides an efficiency factor higher than 95%!

Where is the trade-off, you will ask? Well, fuel is way easier to transport as a source of energy, than electricity, hydrogen, or else. This also impacts the overall mechanical design of the chassis to integrate the batteries, and the thermal chain of everything wich was once based on a heat source (HVAC, heating seats,...).

System integration is key

In a customer project for an automotive supplier, we had to model the dynamic behavior of an electric motor. We reached out to the expertise of our german colleagues from SimulationX.

They have experience with multiple physics, in particular power electronics as well as systems integration, as they participated at the origins of Modelica and the Functional Mock-up Interface standards.

 

Those competencies combined with the integration & deployment capabilities of Scilab enabled to deliver an application tailored to the customer need and integrating within its simulation & test process.

Validate the design before going into production

To conclude on the necessity of our approach in this case, we had to perform the last iterations on the design, before going into production. Those iterations on continuous variables (number of turns of the coil wires) and discrete configurations (number of poles of the stator and the rotor) were impossible to perform dynamically (for a continuous variation of the angular speed of the motor) with a finite element model, because every static configuration (for each angle value) took 3 to 4 hours to compute.

We integrated the simulation results on a given geometry into the system model, and developed a dedicated interface to the model to handle it easily during the test phase:

Read more on the advantages of electric vehicles: 
https://x-engineer.org/automotive-engineering/vehicle/electric-vehicles/advantages-of-electric-vehicles/