Switched predictive control design for optimal wet-clutch engagement

Modeling of hydraulic clutch transmissions is far from straightforward due to their nonlinear hybrid dynamics, i.e. switching between three dynamic phases. In this paper we identify a local linear model only for the constrained first phase, based on which a predictive controller is used to track a suitable engagement signal. The robustness of this controller in the latter two phases is guaranteed by making the constraints inactive and pre-tuning the control parameters based on its closed loop formulation and applying robust stability theorem. This controller is then implemented in real-time on a wet-clutch test setup and is shown to achieve optimal engagement

Smart Traction Control Systems for Electric Vehicles Using Acoustic Road-type Estimation

The application of traction control systems (TCS) for electric vehicles (EV) has great potential due to easy implementation of torque control with direct-drive motors. However, the control system usually requires road-tire friction and slip-ratio values, which must be estimated. While it is not possible to obtain the first one directly, the estimation of latter value requires accurate measurements of chassis and wheel velocity. In addition, existing TCS structures are often designed without considering the robustness and energy efficiency of torque control. In this work, both problems are addressed with a smart TCS design having an integrated acoustic road-type estimation (ARTE) unit. This unit enables the road-type recognition and this information is used to retrieve the correct look-up table between friction coefficient and slip-ratio. The estimation of the friction coefficient helps the system to update the necessary input torque. The ARTE unit utilizes machine learning, mapping the acoustic feature inputs to road-type as output. In this study, three existing TCS for EVs are examined with and without the integrated ARTE unit. The results show significant performance improvement with ARTE, reducing the slip ratio by 75% while saving energy via reduction of applied torque and increasing the robustness of the TCS.Comment: Accepted to be published by IEEE Trans. on Intelligent Vehicles, 22 Jan 201

DIAGRAMS, FUNCTIONAL AND CONSTRUCTIVE SOLUTIONS OF THE STABILITY CONTROL SYSTEMS FOR AUTOMOTIVE APPLICATION

The modern car must correspond to certain requirements regarding the driver safety and more than that it must convince the potential buyer that it will offer him the safety he is so much in need of. For that reason the number and the diversity of the safety systems have increased so fast. Despite all this for the time being it can not be stated that a particular vehicle is totally safe and it can come through any difficult situation. Because of that the research in the field is carried on and the number of those who propose solutions mend to improve the vehicle behavior is getting bigger.active safety, vehicle, control

Adaptive model predictive control for co-ordination of compression and friction brakes in heavy duty vehicles

In this paper, an adaptive model predictive control scheme is designed for speed control of heavy vehicles. The controller co-ordinates use of compression brakes and friction brakes on downhill slopes. Moreover, the model predictive controller takes the actuator constraints into account. A recursive least square scheme with forgetting is used in parallel with the controller to update the estimates of vehicle mass and road grade. The adaptation improved the model predictive controller. Also online estimation of the road grade enhanced the closed-loop performance further by contributing through feedforward control. Simulations of realistic driving scenarios with a validated longitudinal vehicle model are used throughout this paper to illustrate the benefits of co-ordinating the two braking mechanisms and influence of unknown vehicle mass and road grade. Copyright © 2006 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/55894/1/917_ftp.pd

An Integrated Pedal Follower and Torque Based Approach for Electronic Throttle Control in a Motorcycle Engine

Nowadays, electronic throttle control system is widely adapted in the motorcycle for better drivability, fuel economy and reduces the emissions. In such systems, pedal follower or torque based approach are used for calculating the required throttle angle for the given torque demand by driver. This work presents a throttle control system for the precise estimation of throttle angle based on the integrated pedal follower and torque based approach for the given accelerator position and torque demand by the driver. A mathematical model for an electronic throttle body is developed to understand the effects of nonlinearities due to friction and limp home dual springs. A PID controller with compensators are developed to handle the nonlinearities due to the friction and limp home dual springs in the proposed electronic throttle control system. A simulation study has been carried out using software in loop and hardware in loop simulation approaches for step, sinusoidal, and ramp input signals. The responses of electronic throttle body for opening the throttle angle and error are analyzed for the given input signals. The simulation result shows that the proposed compensators has significant advantage in reducing the throttle angle error and gives the desired output

Dynamics of Torque-Speed Profiles for Electric Vehicles and Nonlinear Models Based on Differential-Algebraic Equations

The so-called μ — λ curves, where is the slip ratio and μ is the normalised traction force or the friction index, are nonlinear functions of the velocity of the vehicle and the wheel rotational velocity. Despite their predominant use in the literature, linear approximations of such curves may fail to predict correctly key characteristics of vehicle performance efficiency such as torque-speed profiles. Although attempts to model these characteristics in the context of slip phenomena have been made before, to our best knowledge a general model with respect to the vehicle velocity, the wheel rotating velocity, the slip ratio, the traction force, and the torque, has never been formulated and solved as a coupled nonlinear problem based on a system of differential-algebraic equations arising naturally in this context. In this paper, such a model is formulated, solved numerically, and some results of numerical simulation of driving an electric vehicle on di®erent surface conditions are presented

Design and application of electromechanical actuators for deep space missions

During the period 8/16/92 through 2/15/93, work has been focused on three major topics: (1) screw modeling and testing; (2) motor selection; and (3) health monitoring and fault diagnosis. Detailed theoretical analysis has been performed to specify a full dynamic model for the roller screw. A test stand has been designed for model parameter estimation and screw testing. In addition, the test stand is expected to be used to perform a study on transverse screw loading

Model based control strategies for a class of nonlinear mechanical sub-systems

This paper presents a comparison between various control strategies for a class of mechanical actuators common in heavy-duty industry. Typical actuator components are hydraulic or pneumatic elements with static non-linearities, which are commonly referred to as Hammerstein systems. Such static non-linearities may vary in time as a function of the load and hence classical inverse-model based control strategies may deliver sub-optimal performance. This paper investigates the ability of advanced model based control strategies to satisfy a tolerance interval for position error values, overshoot and settling time specifications. Due to the presence of static non-linearity requiring changing direction of movement, control effort is also evaluated in terms of zero crossing frequency (up-down or left-right movement). Simulation and experimental data from a lab setup suggest that sliding mode control is able to improve global performance parameters

Five-Axis Machine Tool Condition Monitoring Using dSPACE Real-Time System

This paper presents the design, development and SIMULINK implementation of the lumped parameter model of C-axis drive from GEISS five-axis CNC machine tool. The simulated results compare well with the experimental data measured from the actual machine. Also the paper describes the steps for data acquisition using ControlDesk and hardware-in-the-loop implementation of the drive models in dSPACE real-time system. The main components of the HIL system are: the drive model simulation and input – output (I/O) modules for receiving the real controller outputs. The paper explains how the experimental data obtained from the data acquisition process using dSPACE real-time system can be used for the development of machine tool diagnosis and prognosis systems that facilitate the improvement of maintenance activities

The adaptive control system of quadrocopter motion

In this paper we present a system for automatic control of a quadrocopter based on the adaptive control system. The task is to ensure the motion of the quadrocopter along the given route and to control the stabilization of the quadrocopter in the air in a horizontal or in a given angular position by sending control signals to the engines. The nonlinear model of a quadrocopter is expressed in the form of a linear non-stationary system