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

Observer-based, discrete-time, sliding mode throttle control for drive-by-wire operation of a racing motorcycle engine

Abstract\u2014In this brief, the problem of designing a drive-by-wire throttle control system for a high-performance motorcycle engine is considered. Given the characteristics of the electromechanical system to be controlled, an observer-based, discrete-time sliding mode (DTSM) servo controller with integral action is adopted. The controller is designed on the basis of an identified model of the system, whose states are estimated by means of a state observer. Different state observer structures are analyzed, and it is shown that the main characteristics of standard state-feedback-based sliding mode control systems are preserved. A theoretical analysis is also presented showing that a separation principle holds, so that the state observer and the DTSM controller can be designed independently. The performances of the designed controller are illustrated by reporting the results of tests performed on track with a racing motorcycle

Model-Guided Data-Driven Optimization and Control for Internal Combustion Engine Systems

The incorporation of electronic components into modern Internal Combustion, IC, engine systems have facilitated the reduction of fuel consumption and emission from IC engine operations. As more mechanical functions are being replaced by electric or electronic devices, the IC engine systems are becoming more complex in structure. Sophisticated control strategies are called in to help the engine systems meet the drivability demands and to comply with the emission regulations. Different model-based or data-driven algorithms have been applied to the optimization and control of IC engine systems. For the conventional model-based algorithms, the accuracy of the applied system models has a crucial impact on the quality of the feedback system performance. With computable analytic solutions and a good estimation of the real physical processes, the model-based control embedded systems are able to achieve good transient performances. However, the analytic solutions of some nonlinear models are difficult to obtain. Even if the solutions are available, because of the presence of unavoidable modeling uncertainties, the model-based controllers are designed conservatively

Model-Based Control Techniques for Automotive Applications

Two different topics are covered in the thesis. Model Predictive Control applied to the Motion Cueing Problem In the last years the interest about dynamic driving simulators is increasing and new commercial solutions are arising. Driving simulators play an important role in the development of new vehicles and advanced driver assistance devices: in fact, on the one hand, having a human driver on a driving simulator allows automotive manufacturers to bridge the gap between virtual prototyping and on-road testing during the vehicle development phase; on the other hand, novel driver assistance systems (such as advanced accident avoidance systems) can be safely tested by having the driver operating the vehicle in a virtual, highly realistic environment, while being exposed to hazardous situations. In both applications, it is crucial to faithfully reproduce in the simulator the driver's perception of forces acting on the vehicle and its acceleration. This has to be achieved while keeping the platform within its limited operation space. Such strategies go under the name of Motion Cueing Algorithms. In this work, a particular implementation of a Motion Cueing algorithm is described, that is based on Model Predictive Control technique. A distinctive feature of such approach is that it exploits a detailed model of the human vestibular system, and consequently differs from standard Motion Cueing strategies based on Washout Filters: such feature allows for better implementation of tilt coordination and more efficient handling of the platform limits. The algorithm has been evaluated in practice on a small-size, innovative platform, by performing tests with professional drivers. Results show that the MPC-based motion cueing algorithm allows to effectively handle the platform working area, to limit the presence of those platform movements that are typically associated with driver motion sickness, and to devise simple and intuitive tuning procedures. Moreover, the availability of an effective virtual driver allows the development of effective predictive strategies, and first simulation results are reported in the thesis. Control Techniques for a Hybrid Sport Motorcycle Reduction of the environmental impact of transportation systems is a world wide priority. Hybrid propulsion vehicles have proved to have a strong potential to this regard, and different four-wheels solutions have spread out in the market. Differently from cars, and even if they are considered the ideal solution for urban mobility, motorbikes and mopeds have not seen a wide application of hybrid propulsion yet, mostly due to the more strict constraints on available space and driving feeling. In the thesis, the problem of providing a commercial 125cc motorbike with a hybrid propulsion system is considered, by adding an electric engine to its standard internal combustion engine. The aim for the prototype is to use the electrical machine (directly keyed on the drive shaft) to obtain a torque boost during accelerations, improving and regularizing the supplied power while reducing the emissions. Two different control algorithms are proposed 1) the first is based on a standard heuristic with adaptive features, simpler to implement on the ECU for the prototype; 2) the second is a torque-split optimal-control strategy, managing the different contributions from the two engines. A crucial point is the implementation of a Simulink virtual environment, realized starting from a commercial tool, VI-BikeRealTime, to test the algorithms. The hybrid engine model has been implemented in the tool from scratch, as well as a simple battery model, derived directly from data-sheet characteristics by using polynomial interpolation. The simulation system is completed by a virtual rider and a tool for build test circuits. Results of the simulations on a realistic track are included, to evaluate the different performance of the two strategies in a closed loop environment (thanks to the virtual rider). The results from on-track tests of the real prototype, using the first control strategy, are reported too

Study and Performance Enhancement of Fast Tool Servo Diamond Turning of Micro-structured Surfaces

Ph.DDOCTOR OF PHILOSOPH