Analysis and Prospects of Robot Motor Drive and Intelligent Control

Brushless DC motors have become a mainstream trend.

(PS.) Product catalog of CubeMars is listed at the end of this article

Whether it is the motors we see in our daily lives or in various robot lectures, it is not difficult to see that brushless motors are increasingly becoming the trend. For the motors used in robot joints, due to the need for torque feedback and flexible control, DC brushless motors have incomparable advantages over AC permanent magnet synchronous motors. In common consumer products, such as fans, hair dryers, and massage guns, brushless motors surpass brushed motors in terms of lifespan, maintenance cycle, cost, and performance are gradually replacing brushed motors in various applications. However, while the performance of brushless motors can be extremely excellent, they are often limited by their drive and control.

Therefore, this article will explore the future development of brushless motor drive algorithms and the employment and entrepreneurial opportunities in the future motor industry based on the drive and control of brushless motors.

Investigating Factors Restricting the Development of High Power Motor Drivers.

As three-phase motors require AC drive, DC power must be converted to AC power using an inverter circuit, as shown in the figure below. The key factor here is the switches used for commutation. In traditional frequency converters, IGBT drivers are often used as electronic switching devices for frequency conversion. In the case of low DC voltage, field-effect transistors are generally used as switching devices.

Driver heat affects performance.

If applied in the field of robotics to provide a large torque to the motor, field-effect transistors must bear relatively large currents. If the motor is subjected to external forces and rotates in the opposite direction to the driving direction, a large backflow current is generated. To maintain constant force control, a larger current must be supplied to the motor, which means that the field-effect transistor must bear a larger current. Let us do a simple calculation. Assuming that the on-state resistance of the field-effect transistor is 4.xn--5m-fcc, and the current flowing through the drain-source is...

Then, the amount of heat generated by the field-effect transistor within 5 seconds is...

As can be imagined, the heating of the field-effect transistor (FET) is extremely serious under high current conditions. Similarly, for the motor, the continuous variation of the current will cause the motor inductance to generate self-induced electromotive force, which will also affect the current. The heating of the motor internal resistance is also a part that cannot be ignored. Therefore, the first problem faced by brushless motor drives is heat dissipation.

Field-effect transistor overcurrent damage or overvoltage breakdown

In addition, due to the existence of reverse current and locked-rotor current, the performance requirements for FETs are increased. If operating at high speed, FETs with low on-time are required to ensure the frequency of commutation. If operating at high load, it is necessary to ensure that the FETs will not be damaged due to excessive current. Therefore, the performance and cost of FETs are also factors that must be considered in driver design.

In addition, as the field-effect transistor heats up due to thermal effects, the maximum allowable conducting current will also decrease, further increasing the risk of breakdown. Based on current transistor manufacturing technology and the prices of field-effect transistors on the market, the maximum allowable voltage and maximum conducting current directly affect the cost of the transistors. If the current is increased to over 300A, while considering thermal effects and other factors, the cost of using six field-effect transistors would not be less than 80 yuan (RMB). In reality, when driving a brushless motor in a specific direction, the current needed to maintain a constant torque can reach seven times the actual motor current, meaning that for a load that is too large, the field-effect transistor will need to withstand a current of over 350A. The cost of this can be imagined.

The challenges of driving a brushless motor

The voltage between the gate and source of the field-effect transistor determines whether it will turn on or off, which means that certain conditions must be met...

$$

In the bridge inverter circuit, for VT1 in the above figure, the source voltage is the voltage at point a. Therefore, it is required that the gate voltage needs to exceed the sum of the voltage at point a and the threshold voltage to turn on the MOS transistor.

The gate voltage needs to be greater than the sum of the voltage at point a and the threshold voltage for the MOSFET to conduct in the bridge inverter circuit. In order to solve this problem in driving the bridge arm, a bootstrap circuit is often used, as shown in the diagram below.

This diagram is a schematic of the domestically produced EG2312 bridge inverter circuit driver. The use of a bootstrap floating drive power supply greatly simplifies the design of the driving power supply. Only one power supply voltage VCC is required to drive the two power switch devices, the high-end N-channel MOSFET and the low-end N-channel MOSFET, bringing great convenience to practical applications.

In the circuit provided by Yijin Microelectronics, an external bootstrap diode and bootstrap capacitor are used to automatically complete the bootstrap boost function. Assuming that the bootstrap capacitor has been charged to a sufficient voltage during the period when the lower transistor is conducting and the upper transistor is turned off, when the HO pin outputs a high level and the upper transistor is turned on and the lower transistor is turned off, the voltage on the bootstrap capacitor VC will be equivalent to a voltage source as the internal driver VB and VS power supply, completing the drive of the high-end N-channel MOSFET.

Joint motor technology application

The application of joint motors in collaborative robots

The development of collaborative robots

According to the lecture by Midea Robotics and the "2022 China Collaborative Robot Technology Development Report," this article summarizes the development of writing robots in three aspects, as follows:

1. Breakthrough in innovative patented technology for collaborative robots

Several experts compared and analyzed the global patent applications and standards for collaborative robots, as well as the patent layout of key domestic companies such as Jeta Robotics, and discussed the future possibilities for Chinese collaborative robot companies to go global. They also discussed the interpretation of the domestic collaborative robot standard certification system.

2. Collaborative robot certification system is gradually improving

As an important reference for measuring the quality and reliability of robots, the MTDF certification has been widely recognized in industries such as military and aviation. For example, Jieka Robotics has obtained NTBM and SEMI certifications, which are dedicated to improving product quality while ensuring the safety of collaborative robot use.

3. Cutting-edge development trends in collaborative robots

The first cutting-edge trend is intelligent perception and multidisciplinary cross-fusion. As the foundation for the interaction between collaborative robots and human environments or between robots, intelligent perception has become increasingly cross-fused with multiple disciplines. The "2022 China Collaborative Robot Technology Development Report" predicts that the future research direction will be active perception and natural interaction theory and methods, and the addition of more sensors enables collaborative robots to understand human commands.

The second cutting-edge trend is autonomous cognition in complex environments and flexible operation with high intelligence, which is a significant common technology requirement for the new generation of collaborative robots. As the application of collaborative robots becomes increasingly extensive, they need to be more intelligent in terms of complex operating capabilities, adaptive and reconfigurable assembly capabilities, perception capabilities in unstructured environments, and collaboration capabilities with humans. Experts in the "2022 China Collaborative Robot Technology Development Report" predict that the future research direction for collaborative robots will be autonomous cognition in complex environments.

The third cutting-edge trend is the intelligence of human-robot interaction and operation. With the rapid development of human-robot interaction technology, people's requirements for the availability and usability of collaborative robots are increasing. Gesture-based human-robot interaction will become one of the popular research directions for collaborative robot interaction, and human-robot interaction technology will also make significant progress in the coming years.

The fourth cutting-edge trend is collision detection and adaptive and compliant control technology, which will further develop. Collision detection is generally divided into sensor-based collision detection and sensorless collision detection, and the "2022 China Collaborative Robot Technology Development Report" conducted a detailed analysis of the two different collision detection methods. With the transformation and upgrading of the manufacturing industry, collaborative robots can become a key development in intelligent manufacturing due to their many advantages.

The Specific Manifestation of Motor Drive Technology in the Development of Collaborative Robots

An important technology in the development of collaborative robots is flexible control technology, which can be divided into active and passive flexibility, with the key to active flexibility being motor control. According to a lecture by China Science and Technology New Song, sensorless motor technology will inevitably replace sensor-based technology in the future. However, currently, sensorless motor control technology is still relatively immature and difficult to apply at low speeds. Therefore, sensors are often used as an auxiliary solution for sensorless technology.

The implementation method of sensorless technology is achieved through current sampling of the three phases of the motor. When driving the motor, only two of the phases need to be connected with current, and the third phase can be used for measuring the reverse electromotive force. Therefore, by sampling the current of the third phase, the position of the brushless motor rotor can be calculated. However, this method is difficult to implement when the motor rotates at low speeds because the induced electromotive force generated at low speeds is low, and even if it is amplified 200 times by an operational amplifier, it is difficult to avoid errors.

In terms of flexible control, artificial neural networks have gradually been applied. Neural networks have the characteristics of adaptability and self-learning, and are suitable for the research of flexible control of robotic arms, and have great advantages compared with traditional control methods. Research in this area can be broadly divided into two categories: one assumes that the dynamic model of the robotic arm is completely unknown, and the neural network approximates the system's dynamic or inverse dynamic model through learning to achieve feedback control or inverse dynamic control; the other assumes that the dynamic model of the robotic arm is partially known, and the neural network is used to learn the unknown parameters in the model to reduce the burden of online calculation.

In summary, currently, brushless motor sensing technology can basically achieve sensorless flexible control, but for stability reasons, magnetic encoders or photoelectric encoders are often added as an auxiliary. In the future, sensorless brushless motor flexible control will inevitably become the mainstream of control, and intelligent control algorithms based on neural networks can play an important role in it.

Joint motors applied in quadruped robots.

The prospect analysis of quadruped robots based on deep learning.

Quadruped robots use learning-based methods to autonomously learn motion skills and designated tasks. The future development direction of quadruped robots is to tightly integrate the intelligent perception and control capabilities of quadruped robots, so that the intelligent level of quadruped robots can be improved, and they can be deployed in multiple fields. The main application scenarios for future quadruped robots are in the industrial field and the smart home ecosystem.

Application prospects in the industrial field:

Compared with wheeled and tracked mobile robots, quadruped robots have better terrain adaptability and less terrain damage. Compared with other legged robots, they have better stability and higher load capacity. Quadruped robots can replace humans in situations that pose a threat to life safety and complete some tasks. Quadruped robots have rich expansion interfaces on their backs, and after carrying sensing equipment, inspection equipment, and operation terminals, they can complete industrial tasks such as toxic gas detection in underground mines, factory equipment temperature detection, exploration of unknown environments, pipeline and cable inspections, and material transportation.

Application prospects in smart home scenarios:

Quadruped robots have a pet-friendly appearance and can become part of a smart home. Quadruped robots can serve as intelligent pets to accompany children and the elderly, and achieve intelligent emotional interaction with humans through devices such as natural language interaction systems, expression displays, and touch sensors. Learning-based quadruped robots have the ability to autonomously learn motion control strategies and environmental perception capabilities. Robots can carry stereo cameras and lidar sensors to interact with the home environment, learn a variety of flexible and agile motion skills, and achieve intelligent environmental perception. In addition, after connecting to the cloud, the motion strategies learned by individual quadruped robots can be shared with the cloud, and they can also obtain the motion skills of other robots from the cloud, greatly improving the learning efficiency of robots. Quadruped robots based on deep reinforcement learning methods are expected to promote the development of smart homes and the Internet of Things.

Issues with Motor Technology in Quadruped Robots

The bottleneck in high-load, high-torque motors for quadruped robots

As mentioned above, the development of high-power, high-torque brushless motors is limited by power switch components. Therefore, most current quadruped robots use a "motor + reducer" approach to achieve drive. Under heavy loads, the motors of quadruped robots must be able to move smoothly without being reverse-driven, which is very difficult.

Thus, motor drive technology still has a very broad development space in the future. In recent years, many universities and research institutes have also begun to study direct drive motors. If the reducer is a compromise to ensure motor performance, then direct drive technology is an important direction for future development. One of the key issues in solving the problem of direct drive motors is the development of motor drivers.

The Inverter Circuit with N-Channel and P-Channel MOSFETs Fusion

This circuit uses 3 N-type MOSFETs and 3 P-type MOSFETs, which avoids the problem of driving voltage. This is also the solution adopted by the German MK project's ESC. P-type MOSFETs are somewhat similar to PNP transistors, as shown in the figure below. As long as the gate voltage is less than the source voltage (which is negative), and its value is less than a certain negative threshold voltage, the MOSFET's source and drain will conduct, and the current will flow from the source to the drain. Generally, the threshold voltage of P-type power MOSFETs is between -3 to -20V.

Summary:

After analyzing the "HJ Robot Lecture Hall" and various lectures and reviews, this article summarizes the future development prospects of motor drive technology and analyzes the possibility of combining motor control technology with deep learning algorithms. Finally, this article summarizes the following points about future development, entrepreneurship, and employment opportunities:

1. With the continuous development of motor technology, many traditional industries can be replaced by motor technology, such as fitness, massage, human-computer interaction, etc. This may also be a new entrepreneurial opportunity in the future.
2. Brushless motor drive technology still has a lot of room for development. Whether in scientific research or employment, there is a great demand for talent in this field, which is very suitable for consideration by undergraduate graduates.
3. The combination of motor's smooth control technology and artificial intelligence may become a new direction for the development and research of motor control field.
4. The sensorless brushless motor control scheme is currently relatively mature, and the future development space is relatively small. However, this method is still relatively rare in some scenarios, and it is still the main trend in the future.
5. The human-machine interaction of collaborative robots is a specific application of interdisciplinary cross-cutting and a concrete manifestation of society's demand for compound talents in the future. It has certain reference significance for talent training in universities and enterprises.

Looking for a reliable BLDC motor manufacturer?

Look no further than CubeMars! Our high-quality motors are designed to meet your needs and exceed your expectations. Whether you need a motor for industrial, medical, or consumer applications, CubeMars has you covered, and accepting custom designs to meet all your needs! Contact us today to learn more about our products and services.