How to evaluate electric vehicle performance and behavior using simulation
A typical task of a vehicle simulation engineer is to evaluate the effect of different technologies or component selections on overall vehicle performance and behavior. One of the main challenges of this task is the lack of accurate data available for components, especially for engines, batteries, and electric motors. This lack of data availability can lead to false assumptions or extrapolations which may lead to inaccurate results. In this first blog of a two-part series, we will introduce a new integration between GT-SUITE and JMAG-Express Online that provides a method for accurate concept-level electric motor design. In the context of vehicle electrification, motors are a key powertrain component. What is required for a motor is not only high performance as a component but also high consistency with the system. This includes, for instance, matching the motor and battery sizes, but also cooling system size and performance as well. Figure 1 below shows an example of how different losses, and therefore cooling requirements, vary throughout the motor operating range.
High-fidelity efficiency map-based modeling
Vehicle engineers use either a map-based approach measured by the prototype or lower fidelity motor model-based approach at the system design phase. When using a map-based approach, the engineer commonly needs to wait for the prototype to be ready, or relies on other empirical approaches. Alternatively, using a lower fidelity motor model-based approach causes a lot of rework as the design matures. To eliminate these errors and inefficiencies, GT and JSOL have partnered together and are excited to release new software functionality. With GT-SUITE v2020, GT users can now create a high-fidelity motor model by using the embedded JMAG-Express Online interface. JMAG is a comprehensive software suite for electromechanically design and development. It enables users to make a high-fidelity efficiency map model with less than 1% error compared to measurement. It allows the user to see various kinds of motor characteristics within 1 second by changing motor types, slot combinations, dimensions and other machine parameters.
Figure 2 shows a high-level overview of the workflow.
The above workflow is accomplished through an integrated interface, shown in Figure 3.
To the GT user, the experience of concept-level motor design is intuitive and seamless, as well as fast. In this embedded interface, the user has flexibility to change machine types, geometry, as well as requirements for torque, power, and maximum speed. It is also possible to add additional constraints on the system, such as voltage and current limitations, as well as geometry constraints such as maximum motor diameter or stack height, air gap, etc. Based upon “rules of thumb” and common motor design principles, JMAG-Express Online will create a motor which meets the requirements, subject to the constraints. The user can refine the design or proceed with the configured motor design. Because of JMAG’s history in the area of motor design, the end user does not need to be an expert in motor design to be effective in exploring different design possibilities.
Through this embedded workflow, users quickly and efficiently analyze different motor types and create maps for each, such as in Figure 4.
Because the JMAG-Express Online interface is natively integrated with GT-SUITE, users not only analyze the motor behavior in a standalone environment but integrate the JMAG motor models directly in a complete system-level model, as shown in Figure 5.
Such a model can be exercised through standard drive cycles, and by reviewing the residency of plots for motor operating points by going through vehicle simulation, it enables users to reflect immediately on the motor specification and run the next simulations, shown in Figure 6.
By connecting vehicle simulation engineers with parametric and template-driven motor design solutions with JMAG-Express Online, it is now possible to make earlier, and more confident design decisions, or motor selections. The push-button integration allows for design-space studies which more quickly explore all possibilities for the most effective motor solution at the vehicle level. Check out Part 2 of the blog series, where we discuss further integration possibilities between GT and JMAG, which move beyond map-based models into more predictive capabilities.
Written By: Jon Zeman and Yusaku Suzuki