Abstract: This article studies the energy-saving technology of pumping laden electromotor. It adopts fuzzy PID control algorithm in soft programming and two-loop control strategy in hard programming. By controlling the rotational speed of the electromotor, the energy consumption of the pumping-export is reduced to achieve energy-saving and improve the economic benefits of the corporation. Keyword : Fuzzy control; Fuzzy PID algorithm; Programmable logical controller (PLC); Two-loop control Introduction Pumps are general mechanical equipment. Their annual power consumption accounts for about 31% of the national power generation[5]. The uneven load in actual operation accounts for 70%[5]. Because water pumps require high torque from the motor during load startup, a large safety margin is often needed, resulting in oversized motors and a "large horse pulling a small cart" phenomenon. Furthermore, from the perspective of power supply and energy use, researching energy-saving issues for electric motors is of great significance. Addressing the shortcomings of current water pressure regulation systems, this paper proposes a new design scheme for energy-saving motors used in pump loads, employing a highly reliable programmable logic controller (PLC) for automated speed control. In the hardware design, a constant current/constant voltage control module and PLC control technology are used to optimize the hardware circuitry. In the software design, a dual-closed-loop integrated control, a speed inner-loop dual-fuzzy control algorithm, and a water pressure outer-loop fuzzy PID control algorithm are proposed, improving the system's control accuracy and reliability. 1. Hardware Design Scheme To address the shortcomings of current water pressure regulation systems, this design adopts a dual-closed-loop control circuit, consisting of a speed closed loop and a water pressure control closed loop. The design uses an inner loop for pump speed control, with the speed feedback signal taken from a photoelectric encoder mechanically connected to the asynchronous motor. An outer loop for water pressure control uses the outlet pressure signal taken from the pressure sensor at the pump outlet. The main control components selected for this design are as follows: Programmable Logic Controller (PLC): Widely used in industrial production, it significantly improves production efficiency with its extremely short scan cycle and rich performance. It also has strong networking and monitoring capabilities. This system uses the OMRON cx-400 series. Thyristor Intelligent Control Module: Highly integrates the thyristor main circuit and phase-shift control circuit, providing power regulation functions. It also features overheat, overcurrent, and phase loss protection functions. Photoelectric Encoder: Enables high-precision sampling of speed. 1.1 Speed ​​Closed-Loop Design As shown in Figure 1, the speed closed loop uses a photoelectric encoder to sample the speed, obtaining a feedback signal e_n. e_n is compared with the given signal e₀ to obtain the control signal e. This control signal e is input to the PLC input side via an AD/DA converter. The PLC, through a specific control algorithm, automatically adjusts the motor's input voltage according to the load size, ensuring the stator power factor cosφ remains at a high value, thereby improving motor efficiency and achieving energy saving. 1.2 Water Pressure Control Closed-Loop Design A water pump is a torque-reducing load; as the speed decreases, the load torque decreases proportionally to the square of the speed. Let the flow rate of the water pump be Q, the head be H, and the shaft power be P when the motor speed is n. If needed, the motor speed is adjusted to n², then the flow rate becomes Q², the head becomes H², and the shaft power becomes P². From physics, we know that the pump shaft power P is proportional to the cube of the speed n, i.e.: ; the head H is proportional to the square of the speed n, i.e.: ; and the flow rate Q is proportional to the speed n, i.e.: . Clearly, when using speed regulation, if the flow rate Q is to be reduced from 1 to 1/2, it is only necessary to reduce the speed from 1 to 1/2, while the shaft power P is reduced from 1 to (1/2)³, saving 7/8 of the electrical power. Therefore, based on speed control, such as reducing the pump's operating speed, system control can significantly reduce motor shaft power loss, resulting in a very significant energy-saving effect. Furthermore, when the water pressure at the outlet is affected by external disturbances, the higher the pump speed, the smaller the rate of change of the water pressure at the outlet due to the pump speed. In other words, the impact of speed changes on water pressure is smaller when the pump is running at high speed. Therefore, for the automatic water pressure regulation system, to improve system stability and anti-interference capability, this design adopts a closed-loop design for the water pressure outer loop. The water pressure control closed loop is shown in Figure 1. A pressure sensor samples the outlet pressure signal of the pump, outputting the actual water pressure value P. The PLC compares the pump outlet pressure value P with its internally set pressure value to obtain a deviation signal. Then, a fuzzy PID algorithm is used to output a control signal, which is transmitted to the actuator. The actuator adjusts the taps of the three-phase autotransformer to change the input voltage at the motor stator, thereby changing the motor speed and the pump speed, and consequently, the pump outlet pressure. This change is then fed back to the PLC via the pressure sensor, achieving online adjustment of the water pressure P. 2. Software Design Scheme In practice, the controlled system exhibits nonlinearity, time-varying characteristics, and time delay. Furthermore, due to interference from factors such as noise and load disturbances, it is difficult to establish an accurate mathematical model or to alter the mathematical model of the object, resulting in insufficient control accuracy. The fuzzy PID algorithm avoids the need for establishing a mathematical model of the object, achieving fast and high-precision control. Experiments have confirmed that the fuzzy PID algorithm is necessary for situations with large fluctuations in the controlled variable. It enables the controlled variable to be adjusted online in real time to a high precision, thus achieving rapid regulation. 2.1 Speed ​​Closed-Loop Software Design Because the water pump experiences significant fluctuations during operation, especially during startup, a fuzzy algorithm is required. To avoid complex calculations and experiments, this design proposes a dual-fuzzy control algorithm. The universes of discourse for the deviation E, the rate of change of deviation EC, and the control variable U are all set as: E = EC = U = {-3, -2, -1, 0, 1, 2, 3}. The dual-fuzzy control algorithm demonstrates good control performance in this experimental system. It features a very short transition process, with a rotational speed deviation of only ±3‰, and a short PLC operation cycle, significantly reducing the performance requirements of the PLC and saving a substantial amount of hardware investment in practice. This is also the simplest, fastest, and most accurate control algorithm needed in practice. 2.2 Water Pressure Control Closed-Loop Design To improve control accuracy and accelerate system response, the water pressure outer loop adopts a fuzzy PID control strategy, modifying various control parameters based on fuzzy inference and fuzzy logic operation rules. The specific implementation is as follows: Based on the deviation between the detected and actual water pressure values, including positive and negative deviations, the deviations are divided into nine fuzzy subsets: negative large, negative medium, negative small, negative small, zero, positive small, positive small, positive medium, and positive large. Similarly, the rotational speed is divided into six fuzzy subsets based on the rotational speed. Fuzzy control tables are then formed with the water pressure deviation and rotational speed as rows and columns, respectively. Wherein, U(n) — control output of PID controller; e(n) — deviation between system setpoint and sampled value — proportional factor; T — sampling period; — integral time constant; — time constant; Δ — differential operator. Therefore, there are three fuzzy control tables, which control , and respectively. The fuzzy inference rules are as follows: (1) When the water pressure deviation is large (positive and negative), take , so that the integral link fails and the system response speed is accelerated; (2) When the water pressure deviation is quite small (zero), make the regulator output zero; (3) When the water pressure deviation is small, take a smaller value, and vice versa, so that the dynamic and static performance of the system can be taken into account. At the same time, the current speed is considered. When the speed is large, take a larger value to accelerate the system response speed. (4) The role of PID integral is to eliminate static error, but it has hysteresis characteristics. Therefore, when the water pressure deviation is large, take a larger value to reduce the integral effect. Moreover, considering the motor speed, take a smaller value when the speed is low to enhance the integral effect. (5) The role of PID derivative is to accelerate system response, reduce overshoot, and enhance system stability, but it is not conducive to suppressing external interference. Therefore, it is appropriate to increase the derivative when the water pressure deviation is large to enhance the derivative effect. Similarly, increasing it at high speeds is beneficial to improving system performance. 3. Conclusion The energy-saving device for pump-type load motors based on fuzzy control has excellent applicability to systems with small load changes and small speed ranges. It is very suitable for high-pressure water pumps and fans, especially for systems configured with wound-rotor asynchronous motors. Promoting and using this system is a distinctive and effective energy-saving project with significant social and economic benefits. References: [1] Zou Longqing, Chang Yulian, Yang Chao. Research on energy saving and consumption reduction of oilfield water injection system [J]. 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