Xiaogang Wu

Precise position tracking control based on adaptive neuron PID algorithm for automatic clutch driven by DC motor

For automatic clutch control system, precise and quick position tracking is difficult on account of its nonlinear character. A new clutch actuating mechanism with a whirl spring was devised for torque compensation to reduce the load of DC actuator and improve the dynamic performance of clutch control system firstly, and then a neuron adaptive PID controller with feedforward and adjustable gain was designed. The feedforward can accelerate the response of controller, and the weights of neuron adjust automatically through self-learning function so as to obtain adaptive control character, furthermore, PSD (proportion, sum and differentiation) algorithm was proposed to adjust its gain. The experiment results show that the position tracking error is smaller than that of common controller; and the controller can adapt the nonlinear change of clutch load and target engaging speed. It indicates that the controller has good robustness and can meet position tracking control command of clutch.

Estimation of engine torque based on improved BP neural network

Aiming at the mass-energy power assembly control system in HEVs, a method is designed to estimate the engine torque, which is based on improved BP neural network. Based on the experiment results in engine dynamometer, and strong nonlinear characteristic of the engine is taken into account, traditional BP neural network error function is improved, and it is trained by optimal stopping, as a result over-fitting will be avoided. The engine torque output model is established with MATLAB, and it has high estimated accuracy and nice generalization ability. After all, validity of the algorithm mentioned above is verified by experiments.

Simulation research of energy management strategy for range extended electric bus

Based on the analysis of configuration of Range Extended Electric Bus (REEB), the article studies two energy management strategy, which are Charge-Depleting Charge-Sustaining (CDCS) and blended type. On the foundation of creating a vehicle simulation model, the article takes a simulation analysis on the economy of Range Extended Electric Bus. Take the Chinese city bus driving cycle conditions of daily travel mileage 200km for example, the simulation results show that comparing with blended control strategy, Auxiliary Power Unit (APU) application load following control methods with CDCS management strategy have certain improvement on the electric consumption and fuel consumption.

The Economic Analysis of a Plug-In Series Hybrid Electric Vehicle in Different Energy Management Strategy

This paper establishes the system model of a plug-in series hybrid electric vehicle, chooses typical city driving cycle of Chinese passenger vehicle as driving cycle and daily trip mileage of 150km. Two basic energy management strategies of CD-CS and Blended are used to compare the economic indicators of power and fuel consumption. On that basis, this paper summarizes up the fuel economy potential of the plug-in series hybrid vehicles. The simulation results show that, compared with the conventional fuel vehicle, in the driving cycle used in this paper, using CD-CS strategy and APU thermostat control method has the maximum efficiency. If not considering power consumption, the fuel saving ratio can reach 72.98%.

Comparison of different driving cycles control effects of an extended-range electric bus

In order to improve the economy in actual driving cycle of the electric bus, an extended-range electric vehicle (EREV) powertrain system evaluation method based on the characteristics of the driving cycle is proposed. The powertrain simulation model is established. This paper uses the energy management strategies of CD-CS and Blended to simulate and analyze the EREV in the driving cycles of Chinese city and Zhuzhou of Hunan province of China. The simulation results show that the EREV economies are different in different driving cycles. Compared with the conventional diesel bus, if not considering the power consumption, the fuel-saving ratio can reach above 30% in both city driving cycles.

The influence factor analysis of energy consumption on all electric range of electric city bus in China

For the electric city bus demonstration operating in Chinese city, based on establishing the system model, this paper uses constant speed and Hefei of Anhui province of China as driving cycles, mainly analyses the influence of the vehicle mass and the average power of the electric auxiliary on the endurance mileage and energy consumption. Simulation results show that, the electric bus studied in this paper driving at the constant speed of 30km/h, if the vehicle mass increases per 1000kg, the power consumption increases about 3%~4%. If the auxiliary power increases per 5kW, the power consumption increases about 15%~55%. In Hefei city bus driving cycle, if the vehicle mass increases per 1000kg, the endurance mileage decreases about 1km, but the power consumption increases about 3.5%. If the auxiliary power increases per 5kW, the power consumption increases about 22%.

Neural network setting PID control of HEV electronic throttle

Nonlinear motion model of HEV electronic throttle is built. Aiming at the problem that is difficult to set the nonlinear control system optimum parameters for the traditional PID control, and based on the advantages of the fast convergence and strong universal approximation ability of the neural network, the method neural network setting PID control electronic throttle based on the Radial Basis Function is proposed which retain the advantages of traditional PID control, meanwhile, using RBF neural network on-line setting the PID control parameters. The results show that compared with traditional PID control algorithm, the neural network setting PID control algorithm has a stronger adaptability and better tracking effect to the nonlinear of the model.

Control of electromagnetic clutch during vehicles start

While automotive start, there are some problems during clutch jointing control, such as nonlinearity and time-variant. According to partial constant revolution control principle of the engine while vehicle starts, a double closed-loop control system is designed for vehicles with AMT, which is made up of fuzzy turning PID controller and single nerve cell adaptive PID controller. Some experiments are carried out, and the results proved that, there are two obvious benefits of the double closed-loop control system is applied. One is that clutch jointing control is easier, the other is that automotive start more steadily and the sliding friction work is decreasing.