Food Additives,Citric Acid Anhydrous Food Grade,Food Grade Citric Acid Powder,Baking Soda Shaanxi United Xingchuang International Co., Ltd. , https://www.lxcgj.com
System Simulation Journal of Electric Vehicle Brushless DC Motor Drive System Real-time Simulation Lu Zichang, Chai Jianyun, Wang Xiangjie, Qiu Ai Rui (Exciting Electrical Engineering and E-Electronic Technology Department, | Forgive 100084) In the process of designing electric vehicles, Real-time digital simulation can realize parallel engineering, shorten development time, save the pet model, and use Simulink to build a DC-free motor drive system model. It uses dSPACE real-time imitation straight loop automatic 4:i control and controlled object model real-time code. The real-time simulation system has a hardware interface with the actual system, which can be combined with the actual 4 air conditioner or electrical hardware in the loop simulation test or rapid control prototype system. Real-time simulation and real systems.
Assumption: the rotor induced current is negligible, no damper winding, the potential is 120. Difficult, 491,120 tear I is a brushless DC motor is a bifurcation, in the C, system simulation, 圄1 brushless DC motor electronic commutation Main circuit, working waveform and commutation logic voltage; heart, 咚, heart is a, b, c phase potential; 4 is the value of the flat top part of the phase current; I is the value of the 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 mechanical angular velocity; 0 is the rotor electrical angle; L is the potential coefficient; = 2 is the torque coefficient; P is the pole logarithm; Moment and mechanical load torque; / is the rotor moment of inertia. Each phase potential signal is generated by a piecewise linear function based on the magnetic pole position S signal. Brushless DC motors are electronically commutated based on the rotor pole position and appear as a hybrid system of continuous time and discrete events.
According to the above mathematical model, the Simulink frame of the electrical subsystem of the brushless DC motor shown in 圄2 is obtained. The limiter of the é™ é™ limiter is taken as 1/2 to obtain the three-phase potential of the 120. trapezoidal wave. Since the gain attenuation of the limiter is 1/2, in order to obtain the potential center, the center, and the gain of the subsequent series amplifier are taken as 2. 2. Brushless DC motor commutation model The rotor magnetic pole position signal of the brushless DC motor is determined. The phase current phase and frequency, the torque command value determines the phase current amplitude. When the motor is running, the phase current is in phase with the phase potential. Therefore, the positive half-wave value of the phase current during electric operation is fl, f2, f3, f1, f2, and f3 are the magnetic pole position logic signals and their inverted signals.
The phase current negative half-wave value is the phase current full-wave value of which =7; /r, which is the Im value, 7; is 7; When the motor is running, the /m* is reversed and the phase current is inverted from the phase potential (see 1). The magnetic pole position logic signal is developed by the dSPACE real-time system DS1103. The DS1103 board is inserted into the ISA expansion slot of the PC motherboard. The power is supplied by the PC. All models are calculated by the DS1103 in real time, while the dSAPCE test tool software runs on the PC host. .
The dSPACE system I/O hardware model and 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, accessed by the experimental tool software ControlDesk.
With the support of the software ControlDesk, the rapid control prototype or hardware-in-the-loop simulation test of the electric drive system can be quickly realized.圄4 is the Simulink frame of the brushless DC motor drive system established by 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 task, the model has a hardware interface with the actual controller. It can input 6 real PWM pulse signals and output analog signals such as motor electric torque. The upper part is the controller model. As the real-time film 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 measuring model includes a digital incremental encoder model and an analog sinusoidal encoder model. The controller and motor system model implements closed loop through the hardware interface, and operates in asynchronous sampling mode with 72 to form two timer task systems. The real-time motor system model samples the output of the controller, causing a variable delay in the motor system model. To solve the jitter problem caused by this, the sampling rate is set much higher than the sampling rate of 7.
In order to reduce the controller reading the magnetic pole position signal and the commutation control error from the hardware interface, the sampling rate of 72 cannot be too low.
4 Experimental results Real-time simulation system experiment 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 probability of call loss increases monotonously. And the previous stage rises fast, and the latter stage rises slowly. In practical applications, due to the need of QoS, there is often a tolerance for the probability of call loss, corresponding to the maximum acceptable incoming traffic. As the incoming traffic increases from zero, the probability of loss of the loss system rises rapidly and it is likely to reach tolerance soon. If the overhead is allowed, the wait traffic can be considered, and the incoming traffic can continue to increase without exceeding the tolerance. The so-called wait system, that is, when the voice channel is busy, does not immediately abandon the new request information, but is queued for processing. Of course, the wait system increases the average waiting time for users.
When the amount of incoming call A (Murland) m=6, the relationship between the probability of loss of return p and the amount of incoming labor is small. When the system load is small, the effect of improving the carrying capacity of the waiting work is not obvious. In the case of a loss system, the call system can be used in the case where the call is frequent and the talk time is relatively long. When the incoming traffic continues to increase, the system has no additional overhead to maintain a sufficiently long queue, again causing the request to be discarded, such that the probability of call loss exceeds the tolerance. Comparing the two systems, we can see that the waiting system can increase the overhead in a certain amount of traffic, and beyond this range, there is nothing that can be done. In practice, we can balance the processing power and traffic volume of the whole system to the threshold value of the iSS incoming call, the traffic volume during the running process, and the adaptive switching mode between the two modes to play. The best performance of the system.
6 Conclusions The distributed signaling scheme is one of the first choices for many non-central switched network topology. This paper only designs the signaling scheme based on the FSM model for wired shared media, and performs the simulation under CCS. The shared medium discussed in this paper is a bus topology. Further work can be considered on how to implement interconnection between multiple such even heterogeneous subnet junctions. From the perspective of technology development, the concept of distributed switching is also extending to the wireless network, combining software radio technology to multi-hop, hierarchical distributed structure, using spread spectrum multiple access technology to prevent interference and improve the network. The throughput rate is adopted, and the security measures are adopted to improve the security of the network connection, and the multi-service integration such as voice/data, the autonomy of the network management, and the standardization of the signaling scheme are gradually realized.
Real-time simulation of electric vehicle brushless DC motor drive system