Abstract: This paper analyzes the speed synchronization control of multiple motors and introduces the application and control results of PLC and frequency converter technology in the synchronous operation control of vehicles. Keywords: vehicle; speed synchronization control; programmable logic controller; frequency converter 1 Introduction When vehicle drive motors adopt distributed drive, the asynchronous motor speed can lead to uncoordinated vehicle operation, causing the motor speed to deviate from the normal value, and in severe cases, causing equipment damage. Therefore, solving the problem of asynchronous motor speed in distributed drive of vehicle drive motors is of practical significance. This paper introduces an advanced and practical control method using PLC to solve the problem of motor speed synchronization in distributed drive of vehicles. 2 Problem Statement Currently, vehicle operation equipment generally adopts two methods: centralized drive (see Figure 1) and distributed drive (see Figure 2). In centralized drive, the relationship between the frequency converter and the motor is "one-to-many"; in distributed drive, the relationship is "one-to-one". The advantage of "one-to-many" is simple control and convenient operation and maintenance, but the centralized drive layout requires a large space in the vehicle body. When a vehicle has a heavy load or limited space, a distributed drive system ("one-to-one") is typically used due to its compact structure and simple layout. However, this system places high demands on the inverters and motors, particularly regarding synchronization. If the motor speeds are inconsistent, the inverters will work in reverse, resulting in excessive output current and tripping, affecting vehicle efficiency and the lifespan of electrical equipment. Excessive speed deviation can cause vehicle deformation, impacting usability. 3. Solution A PLC and inverter control method is used to achieve synchronous operation of multiple distributed drive motors. The PLC used is a Siemens S7400 series, and Figure 3 shows the network topology. To achieve speed synchronization between the two traction motors, two variable frequency motors are used for traction, and each is controlled by a vector closed-loop speed control system using inverters. The PLC directly controls the two inverters. In the control process, the PLC and inverters are connected via Profibus to ensure the synchronization of the output signal sources. Using the speed of traction motor 1 as the target speed, the speed of traction motor 2 is adjusted by its frequency converter to track the speed of traction motor 1. Two incremental rotary encoders are coaxially connected to the motors, allowing encoder 1 and encoder 2 to collect speed pulse signals from both motors respectively, and send these signals to the high-speed counting module of the PLC. The PLC uses these two speed signal data as input control quantities to perform proportional-integral control (PID) calculations, and the calculation result is sent as an output signal to the PLC's analog module to control the frequency converter of traction motor 2. In this way, the speed of traction motor 2 can be guaranteed to track and change with the speed of traction motor 1, keeping the two speeds synchronized. The pulse signals collected from the encoders are sent to the PLC via the high-speed counting module FM350-1 and converted into motor speed data. The signals from the two motor encoders are compared, and the motor speed difference is adjusted through the PID adjustment module to set the speed value MW1000 for motor 2. MW1000 needs to be converted into a signal that the frequency converter can accept. Since the PLC's corresponding 4-20mA value is 0-27648, and the inverter's receiving range is 0-8192, MW1000/27648×8192 is sent to the analog output channel to be converted into a current signal that the inverter can accept, in order to control the inverter of traction motor 2. PID algorithm is one of the most commonly used mathematical algorithms in industrial control. Its basic formula is as follows: Pou(tt) = K[sub]p[/sub]×(et) + K[sub]i[/sub]×Σ(et) + K[sub]d[/sub]×[ (et) - (et- 1) ] Where: K[sub]p[/sub]—proportional adjustment coefficient. It reflects the system deviation proportionally. Once the system has a deviation, the proportional adjustment immediately produces an adjustment effect to reduce the error. K[sub]i[/sub]—integral adjustment coefficient. It makes the system eliminate steady-state error and improve the accuracy. The strength of the integral action depends on the integral time; the smaller the constant Ti, the stronger the integral action. K[sub]d[/sub]—the derivative adjustment coefficient. The derivative action reflects the rate of change of the system deviation signal, has predictive power, and can predict the trend of deviation changes. Therefore, it can produce an advanced control action, eliminating the deviation before it even forms. To reduce external interference caused by factors such as power system fluctuations, the integral element must be considered when developing the control algorithm. That is, a continuous and stable input signal over a period of time should be used for PID calculation instead of a single instantaneous input signal to eliminate accumulated errors and make the speed adjustable within a certain range. In this way, traction motor 1 and traction motor 2 can be synchronously controlled well with high synchronization accuracy, thus ensuring the stability of the running mechanism. 4 Control Results The PLC host computer monitoring program was developed using STEP7, and WinCC was used to collect speed values ​​and plot curves. The data extraction time interval was 15ms. In reality, traction motor 1 and traction motor 2 have the same speed, but to reflect the tracking and fluctuation of traction motor 2, they are separated here. The speed curve of traction motor 1 is shown above, and the speed curve of traction motor 2 is shown below (see Figure 4). When the speed of traction motor 1 changes, traction motor 2 can respond promptly, track the change, and quickly reach stability. Experiments show that the control method using PLC and frequency converter can achieve high synchronization requirements, with fast response and small speed fluctuation amplitude. 5 Conclusion This control method has been applied in various under-furnace vehicles. In practical applications, the synchronous starting effect is obvious, and the vehicle runs smoothly. Practice has proven that the control method of using PLC to solve the problem of motor speed synchronization when vehicles are driven in a distributed manner has good application effect. It is an ideal speed control method that meets the requirements of production processes, reduces equipment maintenance costs, ensures that vehicles can achieve normal production efficiency, and has significant economic benefits. With the widespread application of PLC and frequency converter control methods, the reliability and flexibility of speed control in the transmission system will be further improved. References: 1. Sun Zengqi et al. Intelligent Control Theory and Technology. Tsinghua University Press, 1997. 2. Chen Chong et al. Microcomputer Control System for Multi-Drive Motor Conveyor Line. Electrical Drive, 1991. 3. Siemens Programming Manual, 2004.