Developing a Dual-Motor EV Control System with Model-Based Design Toolbox
1
Table of Contents
• Introduction
• Overview
• Context
• References
• Conclusion
2
Introduction
This article series presents the Motor Control System (MCS) within an electric vehicle (EV) architecture. It introduces the end-to-end development flow, from controller and plant modeling to simulation, code generation, hardware deployment, and integration with the rest of the vehicle network.
This opening article establishes the technical foundation for a series focused on the architecture, implementation, and integration of a dual-motor control system for EV traction applications.
The series also shows how MathWorks tools can be used together with NXP software and hardware to support a Model-Based Design workflow. This approach helps engineers develop, verify, and deploy motor control applications more efficiently while maintaining traceability across the development cycle.
Figure 1-1. Role of the Motor Control System within the EV traction domain
3
Overview
2.1. What will this series of articles cover?
The articles in this series define the development roadmap for the Motor Control System within a broader EV architecture. The series covers the following topics:
Software and Hardware Environment - Overview of the MathWorks and NXP tools used to develop, test, and validate a dual-motor control system.
Architecture and Model Description - Description of the model architecture, signal interfaces, and core control algorithms implemented in the Motor Control System.
Model-in-the-Loop Development - Simulation of the controller and plant in Simulink to validate algorithms before code generation.
Software-in-the-Loop Validation - Code generation for the validated controller and comparison of the generated software against the Model-in-the-Loop baseline.
Processor-in-the-Loop Validation - Execution of the controller on NXP hardware while the plant remains simulated on the host system.
Deployment and Validation on Real Hardware - Integration with physical hardware, scaling from single-motor to dual-motor operation, and configuration of the NXP MCU peripherals required for motor control.
CAN Integration - Definition of the CAN communication interface, including database design and integration on the target NXP platform.
Results and System Validation - Presentation of the final implementation results and validation of the complete system behavior.
2.2. What is the Motor Control System?
Electric vehicles depend on traction systems that deliver efficient propulsion, accurate torque control, and safe operation. At the center of this functionality is the Motor Control System (MCS), which combines real-time control software, power electronics, sensing, actuation, and communication interfaces into a tightly coordinated embedded system.
Figure 2-1. PMSM motor and controller as core elements of the traction system
In modern EVs, the traction system delivers the torque and power needed to propel the vehicle. It is typically composed of the following elements:
Electric motor - converts electrical energy from the battery into mechanical power at the wheels.
Inverter system - converts DC energy from the battery into the controlled AC waveforms required by the motor.
Transmission system - transfers the generated torque from the motor to the wheels.
At its core, the Motor Control System regulates motor torque, speed, and position by controlling the voltage and current applied to the motor phases. A typical MCS includes the following functional layers:
Control Algorithm - implements torque and current control strategies such as Field-Oriented Control (FOC).
Sensing and Feedback - measures motor currents, voltages, rotor position, and temperature.
Power Electronics - inverter circuitry that switches DC power into AC waveforms for motor drive.
Embedded Processor - microcontroller executing real-time control loops.
Communication Interfaces - CAN, LIN, or Ethernet for integration with other system modules.
Together, these layers form a closed-loop control system that operates at high switching frequencies and under strict real-time constraints.
Figure 2-2. Field-Oriented Control (FOC) architecture
EV traction systems can be implemented using different architectures depending on the required balance of efficiency, performance, cost, and system complexity.
A single-motor architecture uses one traction motor to drive either the front or rear axle. This approach reduces hardware complexity and cost, and it often improves vehicle range because of lower mass and lower overall energy consumption.
A dual-motor architecture uses two independent traction machines that can be arranged in several drivetrain topologies. This configuration enables higher total power, better traction, improved vehicle dynamics, and stronger acceleration. The tradeoff is increased electrical and mechanical complexity, together with higher system cost.
Figure 2-3. Example dual-motor traction architecture
Advantages & Disadvantages of Dual Motor:
Acceleration faster due to torque from both motors
Superior traction and handling, especially in snow, rain or off-road conditions
Slightly lower range due to increased weight and power consumption
More expensive but can include AWD and performance benefits
Advantages & Disadvantages of Single Motor:
Slightly better range due to less energy consumption
More affordable
Moderate traction, suitable for most road conditions
Slower acceleration
Note: The example used throughout this series is based on a dual-motor rear-axle architecture, where each rear wheel is driven by its own motor.
2.3. Target Audience
This series is intended for engineers and technical stakeholders involved in the development, integration, and evaluation of electric drive systems, including the following audiences:
Embedded Software Engineers
Motor Control & Power Electronics Engineers
System Architects & Vehicle Architecture Engineers
Hardware Engineers
Model-Based Design and Simulink Developers
Academic and Research Communities
4
Context
In the electric vehicle architecture presented in this series, the Motor Control System is located in the rear zone of the vehicle. Each rear wheel is driven by an independent Permanent Magnet Synchronous Motor (PMSM). The Motor Control System ECU coordinates both motors and exchanges real-time data with the rest of the vehicle over the CAN network.
Figure 3-1. Motor Control System highlighted within the EV architecture
The traction ECU is built around NXP's S32K396 microcontroller, which supports both single 6-phase motor control and dual 3-phase motor configurations. The inverter stage is driven by the MC33937 pre-driver, which provides three high-side and three low-side FET pre-drivers for automotive motor control applications.
Note: The inverter receives DC power from the vehicle battery, while battery operation and safety are supervised by the Battery Management System.
The Motor Control System communicates over CAN with the Zone Node controller, which in turn exchanges commands and status information with the main vehicle control node responsible for speed and torque requests.
5
References
PMSM Control Workshop
BLDC Control Workshop
A Model-Based Design (MBDT) Environment for Motor Control Algorithm Development
Deploy Motor Control Algorithms on NXP S32K3 from Simulink
Motor Control Rapid Prototyping on NXP S32M2 with MathWorks and Model-Based Design Toolbox
Next Generation of NXP EV Traction Inverter with S32K39 MCU and FS26 SBC
AN14326: 3-phase Motor Control Kit with S32K396 Application Note
AN13884: 3-phase Sensorless PMSM Motor Control Kit with S32K344 using RTD AUTOSAR API Application Note
Advancing Motor Control Performance with Digital Twins
Extended Range Dual-Motor Electric Vehicle Model
6
Conclusion
This article introduced the Motor Control System within an EV architecture and established the technical context for the rest of the series. It explained the role of the Motor Control System, compared single-motor and dual-motor traction topologies, and outlined how a Model-Based Design workflow can be applied using MathWorks tools together with NXP software and hardware.
The next article will focus on the software and hardware environment required to develop, simulate, and deploy the Motor Control System using MathWorks and NXP solutions.
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