Investigation of the passive electromagnetic damper

In this paper, the electromagnetic damper (EMD), which is composed of a permanent-magnet DC motor, a ball screw and a nut, is considered to be analyzed as a passive damper. The main objective pursued in the paper is to determine the EMD characteristics in order to improve the vehicle performance. The effects of the EMD characteristics on ride comfort and road handling are investigated first, and then, the effect of a spring installed in series with the EMD to alter the EMD performance is observed. In order to study energy regeneration, the nonlinear equations of the modified passive electromagnetic suspension system (PEMSS) are extracted. The results of simulation show that the designed passive EMD maintains the desired performance while vibration energy from the road excitation can be regenerated and transformed into electric energy.     

Multi-objective component sizing of plug-in hybrid electric vehicle for optimal energy management

This paper presents a methodology for component sizing optimization of a parallel plug-in hybrid electric vehicle by considering it as a multi-objective optimization problem. In this approach, two objective functions are defined to minimize the drivetrain cost, fuel consumption, and exhaust emissions simultaneously. Also, the driving performance requirements are considered as constraints. In addition, fuzzy logic controller including blended control strategy is developed for the PHEV. Finally, by means of multi-objective particle swarm optimization algorithm, the best choices of components are selected for 32 miles of the both TEH-CAR and UDDS driving cycles. Simulation results demonstrate the effectiveness and practicality of the approach, which prepare different optimal component sizes with various drivetrain costs, equivalent fuel consumption, and exhaust emissions.     

Real-time multi-rate HIL simulation platform for evaluation of a jet engine fuel controller

A new Hardware-In-the-Loop (HIL) platform is developed for testing of a turbojet engine fuel control system using a multi-rate simulation platform. The HIL equipment consists of an industrial PC and a commercial I/O board for jet engine simulation as the controlled process and an Electronic Control Unit (ECU) as the fuel controller. The controlled process consisting of actuator, physical process and sensors is fully simulated in HIL simulation. However, the high resolution signals of some components in the HIL simulation cause the real-time simulation to become difficult due to the need of small time-steps. As a result, the disparity between the jet engine model sampling rate and these high resolution signals requires a multi-rate simulation. In this study, a multi step size simulation is developed using multiple processors. These processors are designed to synchronize the status of the engine model with the control system as well as to convert the raw data of the I/O boards to actual input and output signals in real-time. These features make the HIL equipment more effective and flexible. The HIL environment is proved to be an efficient tool to develop various control functions and to validate the software and hardware of the engine fuel control system.     

Investigation of the Energy Regeneration of Active Suspension System in Hybrid Electric Vehicles

This paper investigates the idea of the energy regeneration of active suspension (AS) system in hybrid electric vehicles (HEVs). For this purpose, extensive simulation and control methods are utilized to develop a simultaneous simulation in which both HEV powertrain and AS systems are simulated in a unified medium. In addition, a hybrid energy storage system (ESS) comprising electrochemical batteries and ultracapacitors (UCs) is proposed for this application. Simulation results reveal that the regeneration of the AS energy results in an improved fuel economy. Moreover, by using the hybrid ESS, AS load fluctuations are transferred from the batteries to the UCs, which, in turn, will improve the efficiency of the batteries and increase their life.      

Time Delay Compensation for Hardware-in-the-loop Simulation of a Turbojet Engine Fuel Control Unit Using Neural NARX Smith Predictor

Hardware-in-the-loop (HIL) simulation is an effective technique that is used for development and testing of control systems while some of the control loop components are simulated in a proper environment and the other components are real hardware. In a conventional HIL simulation, the hardware is an electronic control unit which electronic control signals are communicated between the hardware and the software. But, HIL simulation of a mechanical component requires additional transfer systems to connect the software and hardware. The HIL simulation can achieve unstable behavior or inaccurate results due to unwanted time-delay dynamic of the transfer system. This paper presents the use of Smith predictor for time-delay compensation of transfer system in the HIL simulation of an electro-hydraulic fuel control unit (FCU) for a turbojet engine. A nonlinear auto regressive with exogenous input (NARX) neural network model is used for modeling and predicting the FCU behavior. The neural model is trained by Levenberg-Marquardt algorithm and the training and validation sets are generated using the amplitude modulated pseudo random binary sequence (APRBS). The consistency of the experimental real-time simulation and off-line simulation shows the applicability of the presented method for mitigating the effect of unwanted dynamic of the transfer system in the HIL simulation.