Design of Permanent Magnet Synchronous Motor Control System for Electric Vehicle Air Conditioning Compressor Based on Vector Control

Shi, Kuan; Chen, Yongjun; He, Zhou; Wang, Jie; Li, Yinsheng

doi:10.4236/oalib.1105157

Cited by 8 publications

(7 citation statements)

References 5 publications

(3 reference statements)

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“…where z (1) (k i ) = {z (1) 1 (k i ), z (1) 2 (k i ), … , z (1) n (k i )} is the sequence of immediate mean values of i (1) (k i ), which is also called the sequence of albino background values.…”

Section: Grey Prediction Modelmentioning

confidence: 99%

“…Thus, the sets of albinism equations are shown in Equation (37): (1) 2 (k i ) = b i (0) 3 (k i ) + az (1) 3 (1) n…”

Section: Grey Prediction Modelmentioning

confidence: 99%

“…Permanent magnet synchronous motor (PMSM) is preferentially used in high‐performance systems. It has some significant advantages of good dynamic performance, high efficiency, low copper loss, compact structure, high power density, and high power factor [1–3] and is widely used in aerospace [4], wind turbines [5], servo drive [6], and other fields. The high‐performance PMSM drive system requires the quick current response loop, which guarantees the motor current strictly follows the change of the given value, so as to ensure the stability, high precision, and high dynamic performance.…”

Section: Introductionmentioning

confidence: 99%

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Grey‐prediction‐based double model predictive control strategy for the speed and current control of permanent magnet synchronous motor

Pan

Huang

Guan

et al. 2022

Asian Journal of Control

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To solve the problems of slow response speed of the permanent magnet synchronous motor (PMSM) system when the external disturbance occurs and the poor disturbance rejection performance, a double model predictive control (MPC) strategy for PMSM to control speed and current is proposed in this paper. Further, in order to improve the dynamic performance and disturbance rejection performance of PMSM control system, a grey prediction is introduced, and then a grey‐prediction‐based double MPC strategy is proposed. To be specific, firstly, the mathematical model of PMSM is established under the dq coordinate system, and the traditional control strategy (outer speed loop PI controller and inner current loop deadbeat prediction controller) is elaborated. Secondly, we propose the double MPC strategy where MPC controller is used in the outer speed loop and deadbeat prediction controller is used in the inner current loop. Finally, the grey‐prediction‐based double MPC strategy is proposed where MPC is combined with grey prediction to improve the dynamic performance in the inner current loop. By comparing the traditional control strategy with the double MPC and the grey‐prediction‐based double MPC strategy, the simulation results show that the double MPC and the grey‐prediction‐based double MPC system have no overshoot and the grey‐prediction‐based double MPC system has better steady‐state performance, faster dynamic response and stronger disturbance rejection performance, which proves the effectiveness of the proposed strategy.

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Section: Grey Prediction Modelmentioning

confidence: 99%

“…Thus, the sets of albinism equations are shown in Equation (37): (1) 2 (k i ) = b i (0) 3 (k i ) + az (1) 3 (1) n…”

Section: Grey Prediction Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Grey‐prediction‐based double model predictive control strategy for the speed and current control of permanent magnet synchronous motor

Pan

Huang

Guan

et al. 2022

Asian Journal of Control

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“…In order to carry out the thermal efficiency analysis and performance prediction research of the electric vehicle heat pump air conditioner, the AMESim software environment is used to build the electric vehicle heat pump air conditioner simulation system [7]. AMESim provides a complete system engineering design platform, which can create complex multi-field system models, and perform simulation calculations and in-depth analysis on this basis [8].…”

Section: Establishment Of Simulation Model Of Electric Vehicle Heat Pump Air-conditioning Systemmentioning

confidence: 99%

Intelligent of Electric Vehicle Heat Pump Air Conditioning Control System

Liang-hong

Hou

2021

J. Phys.: Conf. Ser.

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Traditional fuel vehicles consume a lot of fuel and cause serious environmental pollution. At present, when environmental protection is being paid more and more attention, Electric vehicles have received extensive attention from countries all over the world for their advantages in energy safety, environmental protection and long-term development. Electric vehicles have received extensive attention from countries all over the world for their advantages in energy safety, environmental protection and long-term development. With the rapid development of electric vehicles, as the main energy consumer, following the electrical system, the air-conditioning system has become an important factor restricting the power, economy and durability of electric buses. At the same time, compared with the current electric heating PTC method commonly used in electric vehicles, heat pump air conditioners can increase the working range of electric vehicles. Therefore, the application of large-scale energy-saving systems, high-efficiency energy-saving systems, and electric vehicle air-conditioning systems is developed, it is of great significance to the promotion of electric vehicles. This article aims to intelligently study the control system of the electric vehicle air-conditioning heat pump.

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“…Wireless maneuvering control functions, such forward and backward motion or turning in place, are realized through a universal synchronous/asynchronous receiver/transmitter (USART) and a universal serial bus (USB) cable [20], where the control system downloads target files to a custom-made master board to facilitate maneuvering control [21], [22]. The controller program designed to manipulate the USCV remotely according to the three operational modes offers the beneficial features of high-speed response and reliable wireless communication [23]- [25]. The propulsion system achieves articulated USCV motion by employing two submerged pumps as water jet generators [26], with six magnetic valves as the jet controllers.…”

mentioning

confidence: 99%

Control System Design and Thrust Analysis of an Unmanned Surface Cleaning Vessel With a Novel Pump-Valve Propulsion System

Luo

Zheng

et al. 2020

IEEE Access

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This article presents a specialized control system for an unmanned surface cleaning vessel (USCV) employing a pump-valve propulsion system. The system has three operational modes, including manual remote-control mode, self-automated cruise mode, and self-locking remote-control mode. In the manual remote-control mode, users remotely control the vessel by means of a motion-control joystick. In the self-automated cruise mode, the control system is capable of detecting obstacles and automatically controlling the pump-valve propulsion system in response to feedback signals from sensors. The selflocking remote-control mode functions similarly to the first mode, except that the joystick controls the vessel motion in accordance with a single established joystick-actuation pattern. The control system is supported by a commercially available remote controller with wireless communication technology. The functionality of the combined control and pump-valve propulsion system is verified by computational fluid dynamics simulations and experimental tests conducted using a prototype USCV. The combined control and pumpvalve propulsion system is demonstrated to be a cost-effective, simple, and innovative platform that is suitable for use with USCVs. INDEX TERMS USCV, pump-valve propulsion, operational modes, CFD, motion states.

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Design of Permanent Magnet Synchronous Motor Control System for Electric Vehicle Air Conditioning Compressor Based on Vector Control

Cited by 8 publications

References 5 publications

Grey‐prediction‐based double model predictive control strategy for the speed and current control of permanent magnet synchronous motor

Grey‐prediction‐based double model predictive control strategy for the speed and current control of permanent magnet synchronous motor

Intelligent of Electric Vehicle Heat Pump Air Conditioning Control System

Control System Design and Thrust Analysis of an Unmanned Surface Cleaning Vessel With a Novel Pump-Valve Propulsion System

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