This applies especially to closed-loop controllers that get feedback on the output signal and adjust the input power by varying the duty cycle. A duty cycle is the percentage between the current pulse and the complete cycle of the current signal. PWM switching frequency can be different for various applications. Although it should be high enough to prevent power loss. The physical limitations of the stator determine the maximum frequency level. However, there are also the specifications of the control unit itself.
So even if the stator allows you to increase the PWM frequency, you will not be able to do that because of the limited capabilities of your DC brushless motor controller.
As an option, you can employ hysteresis to control the operation of a BLDC motor. This method relates to the sinusoidal commutation too. It allows you to establish the upper and lower limits of the current supplied to the motor. As soon as the current reaches its upper or lower range, the transistor switches turn off or on respectively and change the average current using the law of sines. This is one of the most common dilemmas you might face as you start figuring out how to design a BLDC motor controller.
A discrete circuit can be less reliable since the components should be assembled and soldered onto the board separately. A brushless DC motor controller IC has a smaller size, low production costs, and simplifies the design process.
However, integrated circuits have power limitations. Above that, the failure of one component will lead to the replacement of the entire BLDC motor controller IC, not just this component. Building a brushless DC motor controller circuit, you might come across some challenges. For example, BLDC motor controllers used in power electronics deal with high current and voltage.
They require a high switching frequency. You can achieve this by using either sensor or sensorless measurements.
Position sensors offer a relatively simple detection method that you can implement without sophisticated control algorithms. However, their use complicates the arrangement and maintenance of the motor. The major challenge here is to make the rotor move first, since back EMF will not appear when the rotor is at rest. Thus, the controller will not receive the required information.
So the positioning accuracy will decrease if you run the motor at low speeds. To measure the back EMF correctly, think through your brushless DC motor controller schematic as well as its software. You need to install current and voltage converters, add noise filters, and build digital signal processing DSP algorithms.
Nevertheless, a lot depends on the particular implementation of the measuring method. To achieve improved accuracy, you can combine different techniques. For example, you can use an optical sensor or a rotary encoder together with a Hall-effect sensor. For example, our partners from STMicroelectronics created the STM32 ecosystem for motor control that contains hardware and software development kits, firmware libraries, and other toolsets intended for the design of BLDC motor controllers.
It is necessary for regulating the speed, torque, and other characteristics of the motor. For example, a PID algorithm can process the current speed, compare this value with the setpoint, and define the frequency of the output signals that should be applied to the motor to stabilize its speed. In one of our projects, we created a BLDC motor controller circuit design for a bespoke gear drive. Using a rotary encoder assisted with the positioning task, but the speed control became a challenge.
The difficulty occurred because of the low resolution of the MCU peripherals, namely the timer that generated PWM signals.
To solve this task, we implemented a custom PID algorithm to compensate for the limited range of bits. Brushless DC motors have been in use for over fifty years. The tutorial begins with a discussion on parallel computing - what it is and how it's used, followed by a discussion on concepts and terminology associated with parallel computing. The topics of parallel memory architectures and programming models are then explored.
These topics are followed by a series of practical discussions on a number of the complex issues related to designing and running parallel programs.
The tutorial concludes with several examples of how to parallelize several simple problems. References are included for further self-study. In the simplest sense, parallel computing is the simultaneous use of multiple compute resources to solve a computational problem:. Historically, parallel computing has been considered to be "the high end of computing," and has been used to model difficult problems in many areas of science and engineering:.
Today, commercial applications provide an equal or greater driving force in the development of faster computers. These applications require the processing of large amounts of data in sophisticated ways. For example:. Parallel computers still follow this basic design, just multiplied in units. The basic, fundamental architecture remains the same. Contemporary CPUs consist of one or more cores - a distinct execution unit with its own instruction stream.
Cores with a CPU may be organized into one or more sockets - each socket with its own distinct memory. When a CPU consists of two or more sockets, usually hardware infrastructure supports memory sharing across sockets.
A standalone "computer in a box. Nodes are networked together to comprise a supercomputer. A logically discrete section of computational work. A task is typically a program or program-like set of instructions that is executed by a processor.
A parallel program consists of multiple tasks running on multiple processors. Breaking a task into steps performed by different processor units, with inputs streaming through, much like an assembly line; a type of parallel computing.
Describes a computer architecture where all processors have direct access to common physical memory. In a programming sense, it describes a model where parallel tasks all have the same "picture" of memory and can directly address and access the same logical memory locations regardless of where the physical memory actually exists. Shared memory hardware architecture where multiple processors share a single address space and have equal access to all resources - memory, disk, etc. In hardware, refers to network based memory access for physical memory that is not common.
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