Introduction to Motor Controllers
Controller Design for EVs: Microcontrollers, Sensors, and Driver Circuits
Table of Content: Controller Design Consideration for Electric Motors
- Selection of Appropriate Algorithms
- Ensuring robustness against disturbances and uncertainties
- Thermal management considerations
- Safety and fault detection mechanisms
- How do you design a motor controller for EVs?
- What are the challenges and opportunities for motor controller design for EVs?
The motor controller design involves several aspects, such as the selection of the appropriate motor type and topology, the power electronics components, the microcontroller and the software components, the sensors and the driver circuits, and the communication and networking protocols.
Let’s focus on some of the key considerations for the controller design, such as:
Selection of appropriate control algorithms
The control algorithm is the logic and the mathematical model that determines how the motor controller regulates the power flow and controls the speed and torque of the motor. The control algorithm depends on the type and the characteristics of the motor, the desired performance and robustness, and the computational and hardware resources available.
Some of the common control algorithms for electric motors are:
Field Oriented Control (FOC):
FOC is a vector control method that decouples the stator current of the motor into two components:
the direct current, which controls the flux, and
the quadrature current, which controls the torque.
FOC allows precise and independent control of the speed and torque of the motor and improves the efficiency and the dynamic response. FOC is suitable for AC motors, such as induction motors (IMs) or permanent magnet synchronous motors (PMSMs), and requires a position sensor and a fast microcontroller to implement the coordinate transformation and the current regulation.
Direct Torque Control (DTC):
DTC is another vector control method that directly controls the torque and the flux of the motor, without using a coordinate transformation or a current regulator.
DTC uses a hysteresis controller and a switching table to select the optimal voltage vector for the motor, based on the error between the actual and the reference values of the torque and the flux.
DTC provides fast and robust torque control and eliminates the need for a position sensor and a complex microcontroller. DTC is also suitable for AC motors, such as IMs or PMSMs, but it has some drawbacks, such as high torque ripple, variable switching frequency, and acoustic noise.
Trapezoidal Control:
Trapezoidal control is a scalar control method that applies a constant DC voltage to the motor, and commutates the voltage according to the position of the rotor.
Trapezoidal control provides simple and easy speed control, but it has poor torque control and low efficiency.
Trapezoidal control is suitable for brushless DC motors (BLDCs), which have a trapezoidal back EMF waveform, and require a position sensor and a simple microcontroller to implement the commutation logic.
Sinusoidal Control:
Sinusoidal control is another scalar control method that applies a sinusoidal AC voltage to the motor, and varies the frequency and amplitude of the voltage according to the speed and torque commands.
Sinusoidal control provides smooth and efficient operation, but it has low dynamic response and high computational complexity.
Sinusoidal control is suitable for PMSMs, which have a sinusoidal back EMF waveform and require a position sensor and a fast microcontroller to implement the sinusoidal modulation.
Ensuring robustness against disturbances and uncertainties
The robustness of the motor controller is the ability to maintain the desired performance and stability of the motor, despite the presence of disturbances and uncertainties in the system. Disturbances and uncertainties can arise from various sources, such as the load torque, the motor parameters, the sensor noise, the power supply variations, and the environmental conditions. The robustness of the motor controller can be enhanced by using the following techniques:
Feedback control: Feedback control is the technique of using the measured output of the system, such as the speed or the current of the motor, to adjust the input of the system, such as the voltage or the frequency of the power electronics. Feedback control can compensate for the disturbances and uncertainties in the system, and improve the accuracy and the stability of the motor. Feedback control requires a sensor and a controller to implement the feedback loop.
Feedforward control: Feedforward control is the technique of using the measured or estimated disturbance of the system, such as the load torque or the temperature of the motor, to adjust the input of the system, such as the voltage or the frequency of the power electronics. Feedforward control can anticipate and cancel the effects of the disturbances and uncertainties in the system, and improve the performance and the robustness of the motor. Feedforward control requires a sensor and a controller to implement the feedforward loop.
Adaptive control: Adaptive control is the technique of using the online identification or estimation of the parameters or the states of the system, such as the resistance or the flux of the motor, to adjust the input or the parameters of the controller, such as the voltage or the gains of the regulator. Adaptive control can cope with the variations and the uncertainties in the system, and improve the adaptability and the robustness of the motor. Adaptive control requires a sensor, a controller, and an identifier or an estimator to implement the adaptive algorithm.
Thermal management considerations
The thermal management of the motor controller is the process of controlling the temperature and the heat dissipation of the motor and the power electronics, to ensure the optimal operation and the longevity of the system. The thermal management of the motor controller depends on the following factors:
The power losses and the heat generation of the system: The power losses and the heat generation of the system are the result of the electrical and mechanical inefficiencies of the motor and the power electronics, such as the resistive losses, the switching losses, the core losses, and the friction losses. The power losses and the heat generation of the system depend on the type and the characteristics of the motor and the power electronics, the operating conditions, such as the speed, the torque, the voltage, and the current, and the control methods, such as the switching frequency and the modulation scheme.
The thermal resistance and the heat transfer of the system: The thermal resistance and the heat transfer of the system are the properties that determine how the heat flows from the heat sources, such as the motor and the power devices, to the heat sinks, such as the ambient air or the cooling system. The thermal resistance and the heat transfer of the system depend on the materials and the geometry of the system, the thermal contact and the insulation between the components, and the cooling methods, such as natural convection, forced convection, or liquid cooling.
The temperature and the thermal stress of the system: The temperature and the thermal stress of the system are the effects of the heat distribution and the thermal expansion of the system, which can affect the performance and reliability of the system. The temperature and the thermal stress of the system depend on the thermal equilibrium and the thermal gradient of the system, the temperature limits and the thermal coefficients of the components, and the thermal protection and fault detection mechanisms of the system.
Controller Design Research Papers
Review and Development of Electric Motor Systems and Electric Powertrains for New Energy Vehicles: This paper summarizes the technologies of traction motors, their power electronic controllers, and electric powertrains, and proposes a technology roadmap for the next 15 years
Development of an Advanced Motor Control System for Electric Vehicles: This paper describes how to develop the advanced motor control system for electric vehicles for industrial application. The steady-state and transient performances of this motor control system are analyzed by both test-bench experiments and road experiments
Safety and fault detection mechanisms
The safety and fault detection of the motor controller is the process of ensuring the safe and reliable operation of the motor and the power electronics, and preventing or mitigating the damage or injury caused by the faults or the failures of the system. The safety and fault detection of the motor controller involves the following aspects:
The fault types and the fault causes of the system: The fault types and the fault causes of the system are the classifications and the origins of the abnormal or undesired conditions or events that can occur in the system, such as the overvoltage, the overcurrent, the overtemperature, the short circuit, the ground fault, the open circuit, the sensor failure, or the software error. The fault types and the fault causes of the system depend on the characteristics and the specifications of the motor and the power electronics, the operating conditions, such as the speed, the torque, the voltage, and the current, and the external factors, such as the load, the environment, or the human intervention.
The fault detection and the fault diagnosis of the system: The fault detection and the fault diagnosis of the system are the techniques and the methods of identifying and locating the faults or the failures of the system, based on the observation and the analysis of the signals and the symptoms of the system, such as the voltage, the current, the temperature, or the error codes. The fault detection and the fault diagnosis of the system depend on the sensors and the measurement devices, the fault models and the fault indicators, and the fault detection and diagnosis algorithms, such as the threshold-based methods, the model-based methods, or the artificial intelligence-based methods.
The fault protection and the fault recovery of the system: The fault protection and the fault recovery of the system are the actions and the strategies of preventing or mitigating the consequences and the impacts of the faults or the failures of the system, such as the damage, the injury, or the downtime. The fault protection and the fault recovery of the system depend on the driver circuits and the protection devices, the fault isolation and the fault tolerance mechanisms, and the fault protection and recovery methods, such as the shutdown, the restart, the reconfiguration, or the self-healing.
How do you design a motor controller for EVs?
Choosing the appropriate motor type and topology: The motor type and topology determine the characteristics and requirements of the motor controller. For example, BLDC motors and PMSM motors require a three-phase inverter with six switches to convert the DC voltage from the battery to the AC voltage for the motor. In contrast, induction motors require a variable frequency drive (VFD) to control the frequency and amplitude of the AC voltage. The motor type and topology also affect the size, weight, cost, and efficiency of the motor controller.
Choosing the appropriate control strategy and algorithm: The control strategy and algorithm determine how the motor controller regulates the power flow and controls the motor speed and torque. For example, scalar control, vector control, and direct torque control are some of the common control methods for AC motors, while trapezoidal control, sinusoidal control, and field-oriented control are some of the common control methods for BLDC and PMSM motors. The control strategy and algorithm also affect the performance, complexity, and computational requirements of the motor controller.
Choosing the appropriate hardware and software components: The hardware and software components determine the functionality, integration, networking, and functional safety of the motor controller. For example, microcontrollers (MCUs), gate drivers, power transistors, current and voltage sensors, and communication interfaces are some of the essential hardware components for a motor controller, while firmware, software libraries, and development tools are some of the essential software components. The hardware and software components also affect the motor controller’s power density, reliability, and cost.
What are the challenges and opportunities for motor controller design for EVs?
Increasing the power density and efficiency of the motor controller. As EVs demand higher power and performance from the motor and the battery, the motor controller needs to handle higher currents and voltages, while minimizing the power losses and heat dissipation. This requires the use of advanced power electronics technologies, such as wide bandgap (WBG) materials, such as silicon carbide (SiC) or gallium nitride (GaN), which offer higher switching speeds, lower on-resistance, and higher temperature tolerance than conventional silicon (Si) devices.
Improving the functional safety and reliability of the motor controller. As EVs operate in harsh and dynamic environments, the motor controller needs to ensure the safety and reliability of the system under various conditions and scenarios. This requires the use of robust and redundant hardware and software components, such as isolated gate drivers, bias supplies, current and voltage sensors, and MCUs with functional safety features, such as error correction code (ECC), lockstep cores, and self-test mechanisms.
Enhancing the networking and integration of the motor controller. As EVs become more connected and intelligent, the motor controller needs to communicate and interact with other systems in the vehicle, such as the battery management system (BMS), the vehicle control unit (VCU), and the human-machine interface (HMI). This requires the use of standard and secure communication protocols, such as CAN, LIN, Ethernet, or FlexRay, and the use of modular and scalable hardware and software platforms, such as TI’s C2000™ MCUs, that can support different motor types, topologies, and control methods