New energy vehicles have better clean and environmental protection characteristics than traditional fuel vehicles.The new energy engine cooling technology is critical in the design of new energy vehicles.This paper us...New energy vehicles have better clean and environmental protection characteristics than traditional fuel vehicles.The new energy engine cooling technology is critical in the design of new energy vehicles.This paper used oneand three-way joint simulation methods to simulate the refrigeration system of new energy vehicles.Firstly,a k-εturbulent flow model for the cooling pump flow field is established based on the principle of computational fluid dynamics.Then,the CFD commercial fluid analysis software FLUENT is used to simulate the flow field of the cooling pump under different inlet flow conditions.This paper proposes an optimization scheme for new energy vehicle engines’“boiling”phenomenon under high temperatures and long-time climbing conditions.The simulation results show that changing the radiator’s structure and adjusting the thermostat’s parameters can solve the problem of a“boiling pot.”The optimized new energy vehicle engine can maintain a better operating temperature range.The algorithm model can reference each cryogenic system component hardware selection and control strategy in the new energy vehicle’s engine.展开更多
This paper presents an application of adaptive neural network model-based predictive control (MPC) to the air-fuel ratio of an engine simulation. A multi-layer perceptron (MLP) neural network is trained using two on-l...This paper presents an application of adaptive neural network model-based predictive control (MPC) to the air-fuel ratio of an engine simulation. A multi-layer perceptron (MLP) neural network is trained using two on-line training algorithms: a back propagation algorithm and a recursive least squares (RLS) algorithm. It is used to model parameter uncertainties in the nonlinear dynamics of internal combustion (IC) engines. Based on the adaptive model, an MPC strategy for controlling air-fuel ratio is realized, and its control performance compared with that of a traditional PI controller. A reduced Hessian method, a newly developed sequential quadratic programming (SQP) method for solving nonlinear programming (NLP) problems, is implemented to speed up nonlinear optimization in the MPC. Keywords Air-fuel ratio control - IC engine - adaptive neural networks - nonlinear programming - model predictive control Shi-Wei Wang PhD student, Liverpool John Moores University; MSc in Control Systems, University of Sheffield, 2003; BEng in Automatic Technology, Jilin University, 2000; Current research interests automotive engine control, model predictive control, sliding mode control, neural networks.Ding-Li Yu obtained B.Eng from Harbin Civil Engineering College, Harbin, China in 1981, M.Sc from Jilin University of Technology, Changchun, China in 1986 and PhD from Coventry University, U.K. in 1995, all in control engineering. He is currently a Reader in Process Control at Liverpool John Moores University, U.K. His current research interests are in process control, engine control, fault detection and adaptive neural nets. He is a member of SAFEPROCESS TC in IFAC and an associate editor of the IJMIC and the IJISS.展开更多
To deal with the rate-dependent hysteresis presented in a magnetostrictive actuator, a new method of modeling and control is proposed. The relationship between inputs and outputs of the actuator is approximately descr...To deal with the rate-dependent hysteresis presented in a magnetostrictive actuator, a new method of modeling and control is proposed. The relationship between inputs and outputs of the actuator is approximately described by a dynamic differential equation with two rate-dependent coefficients, each expressed as a polynomial of frequency. For a given frequency, the coefficients will be able to be estimated by approximating the experimental data of the outputs of the magnetostrictive actuator. Based on this model, a quasi-PID controller is designed. In the space of the coefficients and frequency, the stable domain of closed loop system with hysteresis is analyzed. The numerical simulation and experiments have born witness to the feasibility of the proposed new method.展开更多
The paper introduced a special approach for diesel’s all-speed-governor modeling, which, in some cases, could solve the knotty problem frequently met in computer simulation of diesel propulsion system or diesel gener...The paper introduced a special approach for diesel’s all-speed-governor modeling, which, in some cases, could solve the knotty problem frequently met in computer simulation of diesel propulsion system or diesel generating set. Suppose that it is hard to get a control-oriented governor mathematical model when the general approaches, the analytical approach or the experimental approach, are applied, and that an open-loop step response of the diesel engine and its system is available by means of computer simulation, the critical three parameters of a governor mathematical model, the proportional gain K_p, integral time constant K_i, and derivative time constant K_d, can be determined by use of PID tuning method which are widely applied in industrial process control. This paper discussed the train of thought of the approach, precondition, procedure, several modifications of the classical PID model, and some points for attention. A couple of case studies were given to demonstrate the effectiveness of this approach.展开更多
文摘New energy vehicles have better clean and environmental protection characteristics than traditional fuel vehicles.The new energy engine cooling technology is critical in the design of new energy vehicles.This paper used oneand three-way joint simulation methods to simulate the refrigeration system of new energy vehicles.Firstly,a k-εturbulent flow model for the cooling pump flow field is established based on the principle of computational fluid dynamics.Then,the CFD commercial fluid analysis software FLUENT is used to simulate the flow field of the cooling pump under different inlet flow conditions.This paper proposes an optimization scheme for new energy vehicle engines’“boiling”phenomenon under high temperatures and long-time climbing conditions.The simulation results show that changing the radiator’s structure and adjusting the thermostat’s parameters can solve the problem of a“boiling pot.”The optimized new energy vehicle engine can maintain a better operating temperature range.The algorithm model can reference each cryogenic system component hardware selection and control strategy in the new energy vehicle’s engine.
文摘This paper presents an application of adaptive neural network model-based predictive control (MPC) to the air-fuel ratio of an engine simulation. A multi-layer perceptron (MLP) neural network is trained using two on-line training algorithms: a back propagation algorithm and a recursive least squares (RLS) algorithm. It is used to model parameter uncertainties in the nonlinear dynamics of internal combustion (IC) engines. Based on the adaptive model, an MPC strategy for controlling air-fuel ratio is realized, and its control performance compared with that of a traditional PI controller. A reduced Hessian method, a newly developed sequential quadratic programming (SQP) method for solving nonlinear programming (NLP) problems, is implemented to speed up nonlinear optimization in the MPC. Keywords Air-fuel ratio control - IC engine - adaptive neural networks - nonlinear programming - model predictive control Shi-Wei Wang PhD student, Liverpool John Moores University; MSc in Control Systems, University of Sheffield, 2003; BEng in Automatic Technology, Jilin University, 2000; Current research interests automotive engine control, model predictive control, sliding mode control, neural networks.Ding-Li Yu obtained B.Eng from Harbin Civil Engineering College, Harbin, China in 1981, M.Sc from Jilin University of Technology, Changchun, China in 1986 and PhD from Coventry University, U.K. in 1995, all in control engineering. He is currently a Reader in Process Control at Liverpool John Moores University, U.K. His current research interests are in process control, engine control, fault detection and adaptive neural nets. He is a member of SAFEPROCESS TC in IFAC and an associate editor of the IJMIC and the IJISS.
基金National Natural Science Foundation of China (60534020)National Key Project for Basic Research of China (G2002cb312205-02)Key Subject Foundation of Beijing (XK100060526)
文摘To deal with the rate-dependent hysteresis presented in a magnetostrictive actuator, a new method of modeling and control is proposed. The relationship between inputs and outputs of the actuator is approximately described by a dynamic differential equation with two rate-dependent coefficients, each expressed as a polynomial of frequency. For a given frequency, the coefficients will be able to be estimated by approximating the experimental data of the outputs of the magnetostrictive actuator. Based on this model, a quasi-PID controller is designed. In the space of the coefficients and frequency, the stable domain of closed loop system with hysteresis is analyzed. The numerical simulation and experiments have born witness to the feasibility of the proposed new method.
文摘The paper introduced a special approach for diesel’s all-speed-governor modeling, which, in some cases, could solve the knotty problem frequently met in computer simulation of diesel propulsion system or diesel generating set. Suppose that it is hard to get a control-oriented governor mathematical model when the general approaches, the analytical approach or the experimental approach, are applied, and that an open-loop step response of the diesel engine and its system is available by means of computer simulation, the critical three parameters of a governor mathematical model, the proportional gain K_p, integral time constant K_i, and derivative time constant K_d, can be determined by use of PID tuning method which are widely applied in industrial process control. This paper discussed the train of thought of the approach, precondition, procedure, several modifications of the classical PID model, and some points for attention. A couple of case studies were given to demonstrate the effectiveness of this approach.
