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  • National Key Discipline ... Electrification And Automation

  • Mechanical Industry Equipment ... and Facilities Key Laboratory

  • Jiangsu Province Electric ... Drive and Intelligent Control Key Laboratory

  • Jiangsu University & Daqo Group Teaching Demonstration Center

  • Jiangsu Province Advantage Disciplines

Jiangsu Province Electric ... Drive and Intelligent Control Key Laboratory
发布时间:2015-12-08    浏览量:

Laboratory introduction

According to China's major science and technology strategic needs and strategic priorities, the laboratory relies on Jiangsu University, Institute of Electrical and Information Engineering and Automotive Engineering Research Institute in electrical engineering and new energy vehicles in the disciplinary advantage, approved in 2014 in Jiangsu Province, electric vehicle drive Key Laboratory of Intelligent Control.

Laboratory closely follow the current international electric vehicles, rail transportation and other electric vehicles trends and research hot spots, electrical engineering, automotive engineering, control science and engineering for the academic background, focusing on vehicle power and transmission, chassis advanced electronic control, drive motor And systems and other automotive industry product development based on commonalities and cutting-edge technologies, in-depth development of electric vehicle drive and intelligent control of the basic theory and key technologies.

Research direction

Focusing on the practical and industrialized major science and technology issues of electric vehicles, aiming at the theoretical problems and key technologies of electric vehicle driving and control which are urgently needed to be solved, the following aspects are studied and explored.

Research direction: Electric vehicle high-efficiency driving motor and Control According to the electric vehicle drive motor high efficiency, high power density, wide speed range and electric vehicle power performance requirements, based on multi-field analysis, multi-level integration optimization of advanced motor design theory and method, as well as the use of high-density motor limit design To solve the common deep technical problems of motor unit, power electronic unit and integrated optimization of cross-coupling simulation, and to establish the general theory of the design, analysis and control of driving motor for electric vehicle And method. Aiming at the requirements of high dynamic response and constant power speed regulation of electric vehicle drive motor, multi-mode vector control technology is studied to solve the high-speed field weakening stability and precise torque control technology of driving motor and the widening technology of high efficiency energy feedback control area Problem, to achieve precise control of torque within full speed range. The vehicle traction motor and control system reliability in-depth study to improve vehicle drive motor and drive control system reliability. In-depth study of distributed multi-motor independent drive mechanism and multi-motor coordination drive theory and method.

Research direction two: electric vehicle dynamics and advanced control technology According to the structural characteristics of electric vehicles and energy efficient use of comprehensive requirements, considering the nonlinear dynamics of electric vehicles, the uncertainty, the diversity of control variables, control strategies Complexity, in-depth analysis of the new impact of the introduction of electric drive system on vehicle dynamics and other factors to carry out vehicle dynamics theory, methods and key technologies research and development and application to meet the control system robustness, real-time , High dynamic response requirements. In electric vehicle chassis system dynamics and control, the study of electric vehicles tire-road contact conditions identification, non-slip drive control, vehicle lateral dynamics control, chassis integrated control. Research on dynamic performance simulation of electric vehicles, joint recovery of vibration energy and braking energy, matching theory of chassis system and coordination control framework, active / semi-active suspension control, electric power steering control and chassis integrated control are mainly studied. Research on nonlinear dynamics modeling of electric vehicle system, instability mechanism of time-delay system and control method of operation stability, innovative design and integrated control of vehicle chassis system structure based on electromechanical similarity theory, perfect theory of dynamic vehicle performance design and control And method.

Research Direction 3: Flywheel Battery Technology for Electric Vehicles The design and control of bearing support systems and integrated high-speed or ultra-high speed motors restrict the bottleneck of flywheel battery applications. Magnetic bearings are the use of magnetic force to the rotor suspended in space, to achieve no contact between the rotor and stator of a new type of high-performance bearings. In this paper, the dynamic and static loads of flywheel batteries are analyzed. The aim is to reduce the support loss and improve the controllability of bearing force, and to study the five degrees of freedom magnetic suspension bearing and transmission system for flywheel batteries. Research on Particle Swarm Optimization Algorithm for Motor Parameter Design. Research on AC Magnetic Bearings Fast and High Accuracy Strong Tracking Unscented Kalman Filter Sensorless Operation Technique and Method.

Research Interests 4: Interaction of Electric Vehicle Intelligent Information Research Information environment model, information source characteristics, principle and technology of information collection, information fusion method, efficient information transmission technology and energy optimization management system of electric vehicle intelligent information interaction system. Research on the interactive information system of electric vehicle intelligent information to achieve the vehicle information and driver information exchange, vehicle and driving environment information exchange, vehicle traffic environment recognition and multi-information fusion and processing. Research intelligent decision support technology to assess and predict the active safety control, comfort, energy saving and environmental protection performance of the vehicle, focusing on theoretical topics such as multiple information fusion, intelligent decision in modal space and intelligent control of multi-valued evaluation space. Research vehicle energy dynamic management and intelligent integrated control scheme; based on the vehicle internal perception network to obtain the driver operation, vehicle status information of each system, the information fusion to determine the driver's intentions, comprehensive evaluation of the various energy system optimization indicators, coordination of power system components Work to achieve a reasonable switch between the various modes of work and the rational distribution of various types of energy flow to improve the economy of electric vehicles, power and driving comfort.