Model-Based Development


What is required for a motor, which is the key component in vehicle electrification, is not only high performance as a component but also high consistency with the system.
Model-based development using simulation is also becoming indispensable for motor development.
JMAG, which has a high track record in motor design, proposes a new workflow for model-based development.
How the development of motors for EVs will proceed in system design, component design, prototype / performance evaluation, and system verification is presented.
All the examples shown are from simulations using JMAG.

1. System Design

In this phase, with system design, from the performance requirements for the final product to component requirements, that is, motor requirement specifications, are broken down.
The specifications of the motor are determined while confirming that the system requirements are met with heavy use of simulations, where previously motor specifications were determined using experience and rule-based processes. By simulation it is possible to investigate a very large design space at high speed, so it is possible to narrow down the design space more systematically without missing any cases while leaving freedom for a later process.
In system design, from EV requirements, drive motor and drive requirements are deduced. First, after identifying the type of motor and the output based on system requirements, the power flow of candidate motors is examined; and after basic motor requirements are determined, motor type selection is carried out from evaluations of required maximum torque and maximum power. An I-shaped IPM motor is selected for reasons of high efficiency and low magnet quantity (low price).
By examining specific motor geometries and configurations at system design, it is possible to develop efficiently with less rework.

System Design
※You can see the details by clicking on the image or title below.

#01 Verification of cruising distance
#02 Vibration reduction measures
#03 JC08 mode running simulation
#04 Design selection based on maximum output, maximum torque, and maximum efficiency

2. Component Design

Based on the requirements for the motor chosen in the system design in section 1, the specific motor geometry and composition are determined. In this section, the way in which simulation is being used is evolving.
Traditionally, simulation has been used to confirm the performance of motors designed using experience and rules, but with the new workflow, from parametric analysis that makes use of the characteristics of simulation a large design space is searched and the optimum motor meeting the requirements is found.
In this case study rectangular conductors and distributed windings which allow a good fill factor were selected in order to increase the power density. This was done based on the results of parametric analysis for wire type, slot shape, and winding method. Since the rotor has many design variables, from numerous parametric analyses the magnet positioning and geometry was optimized. Taking step skew into account, slot opening width is determined such that cogging torque is minimized. Finally, it is confirmed that the demagnetization resistance is sufficient to withstand even harsh environments.
To adapt control parameters concerning driving a designed motor, detailed motor characteristics are handed over to the control design process.

Component Design
※You can see the details by clicking on the image or title below.

#05 Resistance
#06 Iron loss
#07 Torque
#08 Torque / loss correlation diagram
#09 Cogging torque, induced voltage waveform
#10 Magnet demagnetization and coercive force distribution
#11 Motor characteristics for control design
#12 Calibration of control parameters

3. Prototyping and Tests

What is confirmed during this phase includes the design’s intended performance and whether or not this performance can be demonstrated in actual machines rather than simulations alone, as well as the likelihood of issues occurring.
Today’s latest simulation techniques are run thoroughly through computers using the likes of HPC (High Performance Computing).
Using virtual prototypes results in not only a significant reduction of trial costs, but functions can also be confirmed over a considerably wide range of operation conditions. Elements not usually able to be confirmed in real machines are also observed, such as motor internal magnetic fields, loss, temperature, and force distribution. This offers both a smarter way of confirming functions as well as further ideas for improvement.
 The efficiency map is confirmed here first. Machines can encounter issues in temperature management which can result in substantially time consuming and labor intensive work, but simulations make it possible to generate these issues without difficulty. Magnetic hotspots that cause demagnetization and electromagnetic forces that cause vibrations are analyzed in detail to check that the designed motor satisfies all the required functions.

Prototyping and Tests
※You can see the details by clicking on the image or title below.

#13 Efficiency map
#14 Magnet temperature distribution
#15 Torque ripple
#16,17 Electromagnetic force distribution and eigenmode

4. System Verification

It is confirmed that, when using the motor for production, the final product demonstrates the desired performance.
The control and multiphysics phenomena such as heat and vibration, etc., are confirmed as part of system validation.
MIL/HIL techniques are used for control. Control actions can be validated extensively and in detail using a highly accurate motor model that also captures detailed information such as spatial harmonics, eccentricity, etc., as well as motor magnetic saturation. The integration of physical phenomenon is performed with linked simulations through cooling and sound vibrations. Virtual prototypes and evaluations obtain detailed heat distribution and electromagnetic force distribution which can be transferred to other external 3rd party tools for highly accurate validations.
The corresponding shows the confirmation of electric current and torque responsiveness during times of inverter failure as one example of control validation. This simulation is conducted with JMAG-RT using MATLAB/Simulink. Motor vibration when connected to gears and inverters is also confirmed.

System Verification
※You can see the details by clicking on the image or title below.

#18 ECU control test
#19 Verification of cruising distance
#20 Vibration of Gearbox
#21 Evaluation of Vibrations when Running Vehicle

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