Chien Hsun Wu

Application of a recurrent wavelet fuzzy-neural network in the positioning control of a magnetic-bearing mechanism

A new recurrent wavelet fuzzy neural network (RWFNN) controller is proposed.RWFNN is adopted to control the rotor position of a thrust magnetic bearing (TMB).The online learning algorithm of RWFNN is derived using back-propagation method.The adaptive learning rates are performed via improved particle swarm optimization.Numerical simulations show the validity of TMB using the RWFNN controller. A new recurrent wavelet fuzzy neural network (RWFNN) with adaptive learning rates is proposed to control the rotor position on the axial direction of a thrust magnetic bearing (TMB) mechanism in this study. First, the dynamic analysis of the TMB with differential driving mode (DDM) is derived. Because the dynamic characteristics and system parameters of the TMB mechanism are high nonlinear and time-varying, the RWFNN, which integrates wavelet transforms with fuzzy rules, is proposed to achieve precise positioning control of the TMB. For the designed RWFNN controller, the online learning algorithm is derived using back-propagation method. Moreover, since the improper selection of learning rates for the RWFNN will deteriorate the control performance, an improved particle swarm optimization (IPSO) is adopted to adapt the learning rates of the RWFNN on-line. Numerical simulations show the validity of TMB system using the proposed RWFNN controller with IPSO under the occurrence of uncertainties. Display Omitted

Optimal designs and experimental verification for a hybrid energy storage system

This paper studies the optimal sizing and the experimental verification of a vehicle-used hybrid energy storage system (HESS). To determine the optimized combination that maximizes the traveling distance at an FTP driving pattern, an exhaustive search method was employed. Under constraints of cost, vehicle acceleration, and HESS gross weight, the optimal sizing can be derived. Next, for the purpose of investigating the transient behavior of HESS, equivalent circuits of the lithium battery set and ultracapacitors are proposed. Parameters of all components in circuits can be identified via Nyquist empirical formula and experimental data. An HESS testing platform was established for performance verification. It consists of an HESS, a battery control unit (BMS), power circuits, and an DC Electronic Load. With a supervisory computer, control variables can be adjusted online, while testing data can be retrieved. The results show that using HESS, system performance and battery cycle life will be improved.

System design and mechatronics of an air supply station for air-powered scooters

An air supply station with mechanical and electrical systems was built.Two operation modes were designed for charging air bottles.An air-powered scooter was used to evaluate the design specifications and charging performance.Results confirm that the station produced high-pressure air for vehicles.Theoretical analysis and performance simulation will be conducted in the future. This study developed an air supply station for air-powered scooters. The station comprised mechanical and electrical systems. The key components of the mechanical system were a high-power air compressor, low-pressure cylinder, pneumatic boosting cylinder, high-pressure accumulator, and target tank. The electrical system comprised pressure sensors, air flow sensors, and control circuits, which were equipped adequately for the air charge. An air-powered scooter was used to evaluate the design specifications and charging performance of the station, and the scooter was tested on a chassis dynamometer to assess performance during a modified standard driving cycle. The experimental results confirmed that the air supply station can produce high-pressure air for air-powered vehicles. The station design can guide the development of similar technology by companies in the transportation and green energy industries. Future research will conduct a theoretical analysis by modeling and simulating the performance of the air station and air scooter. Display Omitted

On the study of energy-based control strategy for a lithium battery/supercapacitor hybrid energy storage system

This paper develops an energy-based control strategy for a lithium battery/supercapacitor hybrid energy storage system. The lithium battery set is interconnected in parallel with the supercapacitor module which is linked with a buck-boost converter downstream. The performance maps measured from experiments are utilized to form a control-based nonlinear system model. The control modes can be separated into the hybrid mode and the charging mode. Using. global explorative approach, under various conditions of battery state-or-charge, supercapacitor state-of-charge and loading power, the energy distribution (power split) control can be derived in these two modes. With such energy management, the consumed energy of this hybrid energy storage system is minimized.

An Integrated Optimal Energy Management/Gear-Shifting Strategy for an Electric Continuously Variable Transmission Hybrid Powertrain Using Bacterial Foraging Algorithm

This study developed an integrated energy management/gear-shifting strategy by using a bacterial foraging algorithm (BFA) in an engine/motor hybrid powertrain with electric continuously variable transmission. A control-oriented vehicle model was constructed on the Matlab/Simulink platform for further integration with developed control strategies. A baseline control strategy with four modes was developed for comparison with the proposed BFA. The BFA was used with five bacterial populations to search for the optimal gear ratio and power-split ratio for minimizing the cost: the equivalent fuel consumption. Three main procedures were followed: chemotaxis, reproduction, and elimination-dispersal. After the vehicle model was integrated with the vehicle control unit with the BFA, two driving patterns, the New European Driving Cycle and the Federal Test Procedure, were used to evaluate the energy consumption improvement and equivalent fuel consumption compared with the baseline. The results show that and were improved for the optimal energy management and integrated optimization at the first and second driving cycles, respectively. Real-time platform designs and vehicle integration for a dynamometer test will be investigated in the future.

Intelligent motion control of voice coil motor using PID-based fuzzy neural network with optimized membership function

Purpose The purpose of this paper is to develop a proportional-integral-derivative-based fuzzy neural network (PIDFNN) with elitist bacterial foraging optimization (EBFO)-based optimal membership functions (PIDFNN-EBFO) position controller to control the voice coil motor (VCM) for tracking reference trajectory accurately. Design/methodology/approach Because the control characteristics of the VCM are highly nonlinear and time varying, a PIDFNN, which integrates adaptive PID control with fuzzy rules, is proposed to control the mover position of the VCM. Moreover, an EBFO algorithm is further proposed to find the initial optimal fuzzy membership functions for the PIDFNN controller. Findings Due to the gradient descent method used in back propagation (BP) to derive the on-line learning algorithm for the PIDFNN, it may reach the local optimal solution due to the inappropriate initial values. Hence, a hybrid learning method, which includes BP and EBFO algorithms, is proposed to improve the learning performance of the PIDFNN controller. Research limitations/implications Future work will consider reducing the computational burden of bacterial foraging optimization algorithm for on-line parameters optimization. Practical implications The real-time control system is implemented on a 32-bit floating-point digital signal processor (DSP). The experimental results demonstrate the favorable effectiveness of the proposed PIDFNN-EBFO controlled VCM system. Originality/value A new PIDFNN-EBFO control scheme is proposed and implemented via DSP for real-time VCM position control. The experimental results show the superior control performance of the proposed PIDFNN-EBFO compared with the other control systems.

Mechatronics design and experimental verification of an electric-vehicle-based hybrid thermal management system

In this study, an electric-vehicle-based thermal management system was designed for dual energy sources. An experimental platform developed in a previous study was modified. Regarding the mechanical components, a heat exchanger with a radiator, proportional valve, coolant pipes, and coolant pump was appropriately integrated. Regarding the electric components, two heaters emulating waste heat were controlled using two programmable power supply machines. A rapid-prototyping controller with two temperature inputs and three outputs was designed. Rule-based control strategies were coded to maintain optimal temperatures for the emulated proton exchange membrane fuel cells and lithium batteries. To evaluate the heat power of dual energy sources, driving cycles, energy management control, and efficiency maps of energy sources were considered for deriving time-variant values. The main results are as follows: (a) an advanced mechatronics platform was constructed; (b) a driving cycle simulation was successfully conducted; and (c) coolant temperatures reached their optimal operating ranges when the proportional valve, radiator, and coolant pump were sequentially controlled. The benefits of this novel electric-vehicle-based thermal management system are (a) high-efficiency operation of energy sources, (b) low occupied volume integrated with energy sources, and (c) higher electric vehicle traveling mileage. This system will be integrated with real energy sources and a real electric vehicle in the future.

Development of a real-time simulator for electric vehicle with a Dual Energy Storage System

For verifying the strategy of the Vehicle Control Unit(VCU), a real-time simulation environment needs to be established in advance. It is modified from our in-house simulator for the Electric Vehicle (EV) based on the Hardware in-the-Loop(HIL) structure and constrained by several communication devices, e.g. CAN bus, AI/O, DI/O, etc.. A Dual Energy Storage System (DESS) has been modeled in this simulator. It is composed by a Li-ion battery set and an ultracapacitor in the form of equivalent circuits based on empirical results. Specific driving patterns are utilized as an input to this visual EV simulator. The outputs are the battery SOC, ultracapacitor voltage, energy consumption and the driving mileage. By comparing these outputs of DESS under the giving driving pattern, it could also help determine the combination ratio of the DESS.

Rapid-prototyping designs for the three-power-source hybrid electric scooter with a fuzzy-control energy management

This study mainly develops a hardware-in-the-loop (HIL) platform for a hybrid electric scooter (HES). The fuzzy control strategy is utilized for the energy management among three power sources. A low-order scooter dynamics is constructed including subsystems such as the spark-ignition engine, high-power traction motor, integrated starter-generator (ISG), high-power battery module, transmission, longitudinal vehicle dynamics, etc. For energy management of three power sources, the 73-rule fuzzy control is designed and compared to the traditional rule-based control. Three inputs are the battery state-of-charge (SOC), required torque and engine speed. Three outputs are torque commands for the engine, the motor, and the ISG. The system model and the energy management system are integrated for off-line simulation then. The verified models of control strategy and the vehicle dynamics are downloaded to two real-time simulators for the close-loop control with A/D D/A interface. Simulation results show that the vehicle model details the dynamics of key components, while the energy consumptions of these two control modes are nearly 170kJ under ECE40 driving cycle. This HIL platform can be used for rapid prototyping for vehicle control unit (VCU) designs of HES. The general vehicle model can be extended to various power-level hybrid vehicles with three power sources.

System design and control development for an air/electric hybrid scooter

This paper aimed at developed a power source with the combinaiton of an air motor and a servo motor. The test bench was used to measure the performance curvers and characteristics. The Matlab/Simulink software package was to establish the simulator of the air/electric hybrid powertrain while to analyze the vehicle performance. This research studied the air motor module, the servo motor module, the lithium battery module, the transmission, the energy management strategy, and the driving patterns. The rule-based control strategy was developed; the parameter calibration and rule modification were conducted. The results of simulation and data from the real test were consistent, which indicated that this simulation platform and this approach of performance verification reduces the development period and the cost of trial-and-error experments.