Haobin Jiang

High-Performance Control for a Bearingless Permanent-Magnet Synchronous Motor Using Neural Network Inverse Scheme Plus Internal Model Controllers

This paper proposes a novel decoupling scheme for a bearingless permanent-magnet synchronous motor (BPMSM) to achieve fast-response and high precision performances and to guarantee the system robustness to the external disturbance and parameter uncertainty. The proposed control scheme incorporates the neural network inverse (NNI) method and 2-degree-of-freedom (DOF) internal model controllers. By introducing the NNI systems into the original BPMSM system, a decoupled pseudo-linear system can be constituted. Additionally, based on the characteristics of the pseudo-linear system, the 2-DOF internal model control theory is utilized to design extra controllers to improve the robustness of the whole system. Consequently, the proposed control scheme can effectively improve the static and dynamic performances of the BPMSM system, as well as adjust the tracking and disturbance rejection performances independently. The effectiveness of the proposed scheme has been verified by both simulation and experimental results.

Non-linear modelling and control of semi-active suspensions with variable damping

Electro-hydraulic dampers can provide variable damping force that is modulated by varying the command current; furthermore, they offer advantages such as lower power, rapid response, lower cost, and simple hardware. However, accurate characterisation of non-linear f–v properties in pre-yield and force saturation in post-yield is still required. Meanwhile, traditional linear or quarter vehicle models contain various non-linearities. The development of a multi-body dynamics model is very complex, and therefore, SIMPACK was used with suitable improvements for model development and numerical simulations. A semi-active suspension was built based on a belief–desire–intention (BDI)-agent model framework. Vehicle handling dynamics were analysed, and a co-simulation analysis was conducted in SIMPACK and MATLAB to evaluate the BDI-agent controller. The design effectively improved ride comfort, handling stability, and driving safety. A rapid control prototype was built based on dSPACE to conduct a real vehicle test. The test and simulation results were consistent, which verified the simulation.

Design and experiment study of a semi-active energy-regenerative suspension system

A new kind of semi-active energy-regenerative suspension system is proposed to recover suspension vibration energy, as well as to reduce the suspension cost and demands for the motor-rated capacity. The system consists of an energy-regenerative damper and a DC-DC converter-based energy-regenerative circuit. The energy-regenerative damper is composed of an electromagnetic linear motor and an adjustable shock absorber with three regulating levels. The linear motor just works as the generator to harvest the suspension vibration energy. The circuit can be used to improve the systems energy-regenerative performance and to continuously regulate the motors electromagnetic damping force. Therefore, although the motor works as a generator and damps the isolation without an external power source, the motor damping force is controllable. The damping characteristics of the system are studied based on a two degrees of freedom vehicle vibration model. By further analyzing the circuit operation characteristics under different working modes, the double-loop controller is designed to track the desired damping force. The external-loop is a fuzzy controller that offers the desired equivalent damping. The inner-loop controller, on one hand, is used to generate the pulse number and the frequency to control the angle and the rotational speed of the step motor; on the other hand, the inner-loop is used to offer the duty cycle of the energy-regenerative circuit. Simulations and experiments are conducted to validate such a new suspension system. The results show that the semi-active energy-regenerative suspension can improve vehicle ride comfort with the controllable damping characteristics of the linear motor. Meanwhile, it also ensures energy regeneration.

Low-pass filter based automotive EPS controller and comparative full-vehicle tests

Electric power steering (EPS) has important significance to markedly improve the automotive dynamic performance and static performance, enhance the driverpsilas comfort and security. It also satisfies the demand for environmental protection and energy conservation. The automotive EPS control system was analyzed and the EPS controller was designed based on a new low-pass filter control strategy. Then the full-vehicle test system was established and pylon course slalom tests were performed based on three aspects which were original EPS controller, no EPS controller and self-designed EPS controller. The test results were revealed that the EPS controller self-designed based on the new motor control strategy has marked steering handiness effort and controllability feeling, and can meet the requirement of steering performance. This is the paper style requirement for the Chinese Control and Decision Conference. The writers of papers should and must provide normalized electronic documents in order for readers to search and read papers conveniently.

A High-Performance Control Method of Constant -Controlled Induction Motor Drives for Electric Vehicles

A three-phase induction motor used as a propulsion system for the electric vehicle (EV) is a nonlinear, multi-input multi-output, and strong coupling system. For such a complicated model system with unmeasured and unavoidable disturbances, as well as parameter variations, the conventional vector control method cannot meet the demands of high-performance control. Therefore, a novel control strategy named least squares support vector machines (LSSVM) inverse control is presented in the paper. Invertibility of the induction motor in the constant control mode is proved to confirm its feasibility. The LSSVM inverse is composed of an LSSVM approximating the nonlinear mapping of the induction motor and two integrators. The inverse model of the constant -controlled induction motor drive is obtained by using LSSVM, and then the optimal parameters of LSSVM are determined automatically by applying a modified particle swarm optimization (MPSO). Cascading the LSSVM inverse with the induction motor drive system, the pseudolinear system can be obtained. Thus, it is easy to design the closed-loop linear regulator. The simulation results verify the effectiveness of the proposed method.

Integrated control of lateral and vertical vehicle dynamics based on multi-agent system

The existing research of the integrated chassis control mainly focuses on the different evaluation indexes and control strategy. Among the different evaluation indexes, the comprehensive properties are usually not considered based on the non-linear superposition principle. But, the control strategy has some shortages on tyre model with side-slip angle, road adhesion coefficient, vertical load and velocity. In this paper, based on belief, desire and intention(BDI)-agent model framework, the TYRE agent, electric power steering(EPS) agent and active suspension system(ASS) agent are proposed. In the system(SYS) agent, the coordination mechanism is employed to manage interdependences and conflicts among other agents, so as to improve the flexibility, adaptability, and robustness of the global control system. Due to the existence of the simulation demand of dynamic performance, the vehicle multi-body dynamics model is established by SIMPACK. And then the co-simulation analysis is conducted to evaluate the proposed multi-agent system(MAS) controller. The simulation results demonstrate that the MAS has good effect on the performance of EPS and ASS. Meantime, the better road feeling for the driver is provided considering the multiple and complex driving traffic. Finally, the MAS rapid control prototyping is built to conduct the real vehicle test. The test results are consistent to the simulation results, which verifies the correctness of simulation. The proposed research ensures the driving safety, enhances the handling stability, and improves the ride comfort.

Fuzzy Chaos Control for Vehicle Lateral Dynamics Based on Active Suspension System

The existing research of the active suspension system (ASS) mainly focuses on the different evaluation indexes and control strategies. Among the different components, the nonlinear characteristics of practical systems and control are usually not considered for vehicle lateral dynamics. But the vehicle model has some shortages on tyre model with side-slip angle, road adhesion coefficient, vertical load and velocity. In this paper, the nonlinear dynamic model of lateral system is considered and also the adaptive neural network of tire is introduced. By nonlinear analysis methods, such as the bifurcation diagram and Lyapunov exponent, it has shown that the lateral dynamics exhibits complicated motions with the forward speed. Then, a fuzzy control method is applied to the lateral system aiming to convert chaos into periodic motion using the linear-state feedback of an available lateral force with changing tire load. Finally, the rapid control prototyping is built to conduct the real vehicle test. By comparison of time response diagram, phase portraits and Lyapunov exponents at different work conditions, the results on step input and S-shaped road indicate that the slip angle and yaw velocity of lateral dynamics enter into stable domain and the results of test are consistent to the simulation and verified the correctness of simulation. And the Lyapunov exponents of the closed-loop system are becoming from positive to negative. This research proposes a fuzzy control method which has sufficient suppress chaotic motions as an effective active suspension system.

Path Tracking Control of Automatic Parking Cloud Model considering the Influence of Time Delay

This paper establishes the kinematic model of the automatic parking system and analyzes the kinematic constraints of the vehicle. Furthermore, it solves the problem where the traditional automatic parking system model fails to take into account the time delay. Firstly, based on simulating calculation, the influence of time delay on the dynamic trajectory of a vehicle in the automatic parking system is analyzed under the transverse distance between different target spaces. Secondly, on the basis of cloud model, this paper utilizes the tracking control of an intelligent path closer to human intelligent behavior to further study the Cloud Generator-based parking path tracking control method and construct a vehicle path tracking control model. Moreover, tracking and steering control effects of the model are verified through simulation analysis. Finally, the effectiveness and timeliness of automatic parking controller in the aspect of path tracking are tested through a real vehicle experiment.

Night-Time Vehicle Detection Algorithm Based on Visual Saliency and Deep Learning

Night vision systems get more and more attention in the field of automotive active safety field. In this area, a number of researchers have proposed far-infrared sensor based night-time vehicle detection algorithm. However, existing algorithms have low performance in some indicators such as the detection rate and processing time. To solve this problem, we propose a far-infrared image vehicle detection algorithm based on visual saliency and deep learning. Firstly, most of the nonvehicle pixels will be removed with visual saliency computation. Then, vehicle candidate will be generated by using prior information such as camera parameters and vehicle size. Finally, classifier trained with deep belief networks will be applied to verify the candidates generated in last step. The proposed algorithm is tested in around 6000 images and achieves detection rate of 92.3% and processing time of 25 Hz which is better than existing methods.

Crystal structure and electrochemical performance of La0.75Ce0.25Ni3.46-Al0.17Mn0.04Co1.33 alloy for high-power-type 29 Ah Ni-MH battery

Abstract An AB 5 type alloy, La 0.75 Ce 0.25 Ni 3.46 Al 0.17 Mn 0.04 Co 1.33 , was successfully prepared via partial substitution of Ce for La and Al, Mn, Co for Ni, respectively. The structure, morphology, and chemical composition of the as-obtained alloy powders were carefully examined by X-ray diffraction, scanning electron microscopy equipped with energy dispersive X-ray spectroscopy. Electrochemical properties of the hydrogen storage alloy were systematically investigated in standard 29 Ah Ni-MH batteries. The 29 Ah Ni-MH battery exhibited a theoretical discharge capacity of 29 Ah at 1 C. The capacity retention was 99% after 2000 cycles. Furthermore, excellent low temperature performance of this hydrogen storage alloy was obtained at −25 °C. And the results showed that it exhibited not only high discharge capacity (21 Ah at −25 °C and 1 C), excellent high current densities instantaneous discharge performance (discharge 0.9 Ah in 10 s at 12.5 C rate and the voltage could be maintained around 0.73 V), but also remarkable high-rate discharge capacity (discharge 17.7 Ah at 50% SOC and 6.25 C, and the voltage could be maintained around 0.95 V).