Real-time Simulation of Brushless DC Motor Drive System for Electric Vehicles

Simulation of Brushless DC Motor Drive System for Electric Vehicles Lu Zichang, Chai Jianyun, Wang Xiangjie, Qiu Arui (Electrical Engineering of Jilin Electrical Engineering and E Yong, | è°…100084) Real-time digital simulation can realize concurrent engineering, shorten development time, save open modeling Simulink establishes no DC motor drive system model, adopts dSPACE real-time imitation loop automatic 4:i control and real-time code of controlled object model. The real-time simulation system has a hardware interface with the actual system, which can be combined with an actual four-air conditioner or an electrical hardware to form a loop-based simulation test or a rapid control prototype system. Real-time simulation and real systems.

Assumed: rotor inductive current is negligible, non-damped windings, potential is 120. Li-Tian Li, 491120 Tears I is a brushless DC motor is a bifurcation, in C, C system simulation 圄 1 brushless DC motor electronic commutation Main circuit, working waveform and commutation logic pressure; heart, enthalpy, heart is a, b, c phase potential; 4 is the value of phase current flat top part; I is the value of potential flat top part; where is the stator phase resistance, k is the stator phase self-inductance and stator phase mutual inductance; L is the rotor electrical angular velocity and the mechanical angular velocity; 0 is the rotor electrical angle; L is the potential coefficient;=2 is the torque coefficient; P is the number of pairs of poles; Moment and mechanical load torque; / Rotor inertia. Based on the pole position S signal, each phase potential signal is generated by a piecewise linear function. Brushless DC motors are electronically commutated based on the rotor pole position and represent a mixture of continuous and discrete events.

According to the above mathematical model, the Simulink box of the brushless DC motor electrical subsystem is shown in 圄2. The limiting value of the middle limiter is set to 1/2 to obtain 120. Three-phase potential of the trapezoidal wave. Since the gain limiter of the limiter is reduced by 1/2, the gain of the potential center, the heart, and the gain of the subsequent series amplifier are taken as 2. 2. The rotor pole position signal of the brushless DC motor is determined by the commutation model of the brushless DC motor. The phase current and frequency of the phase current determine the phase current amplitude. When the electric motor is running, the phase current is in phase with the phase potential. Therefore, the positive half-wave value of the phase current during the electric operation is f1, f2, f3, f1, f2, f3 as the magnetic pole position logic signal and its inverse signal.

The negative half-wave value of the phase current is the full-wave value of the phase current where =7;/r, which is the Im value, 7; 7; When the motor generates power, the /m* is inverted and the phase current is in phase opposition with the phase potential (see 1). The magnetic pole position logic signal is developed by dSPACE real-time system DS1103. The DS1103 board is plugged into the expansion slot of the PC board ISA. The power is supplied by the PC. All models are executed in real time by the DS1103. The dSAPCE test tool software runs on the host PC. .

The dSPACE system I/O hardware model and the real-time operating system kernel can automatically generate the target system real-time code from the application system Simulink model. Real-TimeInterface also generates a variable file based on signals and parameters, which is accessed by the experimental tool software ControlDesk.

With the support of the software ControlDesk, it is possible to quickly implement a prototype or hardware-in-the-loop simulation test of an electric drive system.圄4 is a Simulink box for a brushless DC motor drive system built using the above motor model and dSPACE system I/O hardware model. The lower part of the crucible is a brushless DC motor system model. As a real-time service model, the model has a hardware interface with the actual controller, which can input 6 real PWM pulse signals and output analog signals such as motor electrical torque; the upper part is the controller model. As a real-time membrane r2, PWM is generated by the DSP controller F240 hardware, and the bottle uses the PWM signal as the controller sampling timing.

The converter adopts a switching function modeling method, and the speed measurement model includes a digital incremental encoder model and an analog sinusoidal encoder model. The controller and the motor system model are closed-loop via a hardware interface, and 72 work in an asynchronous sampling mode to form a two-timer mission system. The sampling of the output of the controller by the real-time motor system model will cause a variable delay of the motor system model. In order to solve the jitter problem caused by this, the sampling rate set is far higher than the sampling rate of 7.

In order to reduce the controller from reading the magnetic pole position signal and the commutation control error from the hardware interface, the sampling rate of 72 must not be too low.

4 Experimental results Real-time simulation system experiments For the hybrid electric vehicle brushless DC motor drive system we developed, the inverter parameters: 1200V, 300A, PWM switch with the increase of incoming traffic, the call loss probability monotonous rise. In the previous period, it rose quickly, and in the later period it rose slowly. In practice, due to the need of QoS, there is often a tolerance for the call loss probability, corresponding to the maximum acceptable incoming traffic. As the incoming traffic increases from zero, the loss probability of the loss system rises rapidly, and the tolerance may soon be reached. If the system overhead allows it to be considered, the incoming traffic can continue to increase without exceeding the tolerance. The so-called waiting system, that is, when the voice channels are all busy, they do not immediately discard the new request information, but instead form queues waiting to be processed. Of course, the waiting system increases the average waiting time for users.

The relationship between the call loss probability p and the incoming call volume when the incoming call volume A (Jauerland) m = 6 is small. When the system load is small, the effect of improving the carrying capacity of the call waiting service is not obvious. For the sake of convenience, the system of loss can be used. On the contrary, if the call is frequent and the talk time is relatively long, it is suitable to use the wait system. When the incoming traffic continues to increase, the system has no additional overhead to maintain a long enough queue, again causing the request to be abandoned, so that the call loss probability exceeds the tolerance. Comparing the two systems, it can be seen that the wait system can increase the additional expenses to a certain extent within the scope of the traffic to compensate for the shortcomings of the system. If it exceeds this range, it will be powerless. In practice, iSS can be used to input the critical value of a call by weighing the processing capacity and traffic volume of the entire system. During the operation, the traffic volume is small, and the mode of switching between the two modes is adaptive to exert The best performance of the system.

6 Conclusions The distributed signaling scheme is one of the first choices for many topologyless switching fabrics. This paper only focuses on wired shared media. The signaling scheme is designed by the FSM model, and the simulation under CCS is performed. The shared media discussed in this article is a bus topology. Further work can consider how to implement interconnection and intercommunication between multiple such or even different subnet connections. From the perspective of technology development, the concept of distributed switching is also extending to wireless network nodes. It combines software radio technology to enable it to evolve to multi-hop and hierarchical distributed architectures. It adopts spread spectrum multiple access technology to resist interference and improve network performance. With regard to throughput, security measures are adopted to improve network security, and the integration of voice and data services, the autonomy of network management, and the standardization of signaling schemes are gradually realized.