An investigation into hybrid power trains for vehicles with regenerative braking

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Adaptive-smith predictor for controlling an automotive electronic throttle over network

The paper presents a control strategy for an automotive electronic throttle, a device used to regulate the power produced by spark-ignition engines. Controlling the electronic throttle body is a difficult task because the throttle accounts strong nonlinearities. The difficulty increases when the control works through communication networks subject to random delay. In this paper, we revisit the Smith-predictor control, and show how to adapt it for controlling the electronic throttle body over a delay-driven network. Experiments were carried out in a laboratory, and the corresponding data indicate the benefits of our approach for applications.Peer ReviewedPostprint (published version

Smart materials and vehicle efficiency. Design and experimentation of new devices.

In this dissertation the activities carried out during the PhD are comprehensively described. The research mainly focused on the development of novel smart devices aimed at disengaging auxiliaries in internal combustion engine vehicles. In particular, the activities dealt with modeling, design, manufacturing and testing different fail-safe magnetorheological clutch prototypes, in the framework of a project funded by Regione Toscana, which involved two departments of the University of Pisa and Pierburg Pump Technology - Stabilimento di Livorno. After an extended literature review, several concepts of the clutch were proposed, which led to the design of the first magnetorheological prototype. An intensive experimental campaign was conducted, which involved several prototypes. A particular attention was focused on the measurement and analysis of the torque transmitted by the clutch in different operating conditions and new indices were proposed to objectively analyze the performances of magnetorheological clutches in general. On the basis of the results of the first experimental phase, the limits of the first design were analyzed and a novel prototype was developed, which succeeded in fulfilling all the design specifications. Further analyses were carried out in order to develop a clutch model starting from the experimental results. The effect of clutch heating was considered and a complete model of the clutch based on neural networks was proposed. The model was capable of taking into account the effect of the main parameters influencing the torque characteristic and may be used in a vehicle simulator or in a hardware-in-the-loop bench. Finally, an additional component to be connected to the clutch, which made use of shape memory alloys, was developed and tested during the visiting period at the University of Toledo (OH), USA

Dry Clutch Modeling, Estimation, and Control

A Doctor’s degree comprises 240 ECTS credits (4 years of full-time postgraduate studies), of which at least 120 ECTS credits constitute a doctoral dissertation

MODELING AND ANALYSIS FOR DRIVELINE JERK CONTROL

In modern-day automotive industry, automotive manufacturers pay keen attention to driver’s safety and comfort by ensuring good vehicle drivability, feel of acceleration, limiting jerk and noise. The vehicle driveline plays a critical role to meet these criteria. By using high-fidelity simulation tool such as AMESim®, it is now possible to accurately model the vehicle driveline to be tested for different scenarios. With Simulink®, one can develop an efficient torque-based control system to limit the driveline oscillations and the generated noise. So, a joint simulation is used which provides a platform to evaluate the estimators and control system while considering the fast dynamics of the non-linear system. This report presents the detailed driveline model developed to evaluate the important parameters which affect the driveline of a pickup truck. The model is developed considering the non-linear dynamics of the driveline, torque converter clutch dynamics and the non-linearities in the propeller shafts and the drive-shafts. It is then evaluated at different input conditions for two major test scenarios – tip-in and tip-out. Both scenarios show that the model displays the transmission and final drive backlash dynamics as anticipated in practical scenarios. The wheel speed shown by the results of the model proves that stiffness and damping coefficient of the tires play an important role in predicting the physical behavior of the vehicle. In addition, for the case of a tip-in from negative to positive torque, the effect of flexibilities of the driveshafts is shown as significant by this model. The oscillations caused due to these flexibilities are within 7 – 8 Hz range for evaluation at fifth gear. This frequency of oscillations found in this model is comparable to the results found in the literature. In future, experimental validation of the current full-order model would provide a better understanding of the assumptions considered while developing it. A reduced order model can be derived from the current model which can be further used to develop the estimators and controllers for active reduction of the driveline oscillations. Also, the overall effect of engine mounting system, comprehensive tire model and suspension dynamics on driveline oscillation can be studied

Tribological And Dynamical Study Of An Automotive Transmission System

The transmission system is critical for automotive and heavy duty equipment due to its prominent role in the powertrain system, which is often challenged with degraded torque capacity and harsh dynamic response. Simulation-guided design can provide appropriate guidelines to resolve these problems with virtual analyses. In current study, the tribological and dynamical study of an automatic transmission is performed at two levels: a wet clutch and powertrain. In this dissertation, tribological study is performed for a wet clutch based on the thermohydrodynamic (THD) analysis that takes the following factors into account. • The groove effect (depth, area, and pattern) is investigated for lubrication analysis; • The elastic-plastic asperity contact model is used to predict the contact pressure; • The heat transfer during the entire cycle of engagement from slip to lock to detachment is covered; • The engagement time and the temperature profile are predicted for torque and thermal analysis. With large engagement cycles, the friction lining of a wet clutch is worn off due to the material degradation at high load/temperature condition. By relating the wear behavior with the mechanism of thermal degradation and thermomechanical degradation, a physics-based wear model is proposed for the first time to analyze the wear process in a wet clutch. The predicted wear rate falls within nearly 95% confidence interval of the test results. Discrepancies of simulation are primarily due to limited availability of input data and model assumptions. Therefore, an uncertainty quantification analysis of the wear model is performed using the Monte Carlo simulations. In addition, a comprehensive parametric analysis of the clutch wear is considered with various factors, including groove design (waffle pattern shows the minimum wear), material properties and operational configurations (rotational speed plays the most influential role). The dynamics of transmission directly affects the performance of the powertrain. The coupling effects of the key transmission components are examined. Of particular interests are the stick-slip behavior of the wet clutch and backlash of the gear train. Through simulation of the powertrain, the main source and the pattern of vibration propagation in the driveline are examined. Major vibration is observed during inappropriate clutch engagement

Operation Simulation and Control of a Hybrid Vehicle Based on a Dual Clutch Configuration

Today, the world thrives on making more fuel-efficient vehicles that consume less energy, emit fewer emissions and have enhanced overall performance. Hybrid Electric Vehicles (HEVs) offer the advantages of improved fuel economy and emissions without sacrificing vehicle performance factors such as safety, reliability and other features. The durability and performance enhancements of HEVs have encouraged researchers to develop various hybrid power-train configurations and improve associated issues, such as component sizing and control strategies. HEVs with dual clutch transmissions (HDCT) are used in operation modes to improve fuel efficiency and dynamic performance for both diesel engines and high-speed gas engines. Dual clutch transmissions (DCTs) are proved to be the first automatic transmission type to provide better efficiency than manual transmissions. DCTs also provide reduced shift shocks and shift time that result in better driving experience. In addition, advanced software allows more simplistic approaches and tunable launch strategies in HDCT development. In this dissertation, an innovative approach to develop a desired mode controller for a HDCT configuration is proposed. This mode controller allows the driver to select the desired driving style of the vehicle. The proposed controller was developed based on adaptive control theory for the overall HDCT system. The proposed Model Reference Adaptive Control (MRAC) was applied to a parallel hybrid electric vehicle with dual clutch transmission (HDCT), and yielded good performance under different conditions. This implies that the MRAC is adaptive to different torque distribution strategies. The current study, which was performed on adaptive control applications, revealed that the Lyapunov method was effective and yielded good performance. The MRAC method was also applied to the mode transition of an HDCT bus. The simulation results confirmed that the MRAC outperformed the conventional operation method for an HDCT with reduced vehicle jerk and the torque interruption for the driveline and with improved fuel efficiency.Ph.D.College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttps://deepblue.lib.umich.edu/bitstream/2027.42/145173/1/Final Dissertation Elzaghir.pdfDescription of Final Dissertation Elzaghir.pdf : Dissertatio

Model-based control for automotive applications

The number of distributed control systems in modern vehicles has increased exponentially over the past decades. Today’s performance improvements and innovations in the automotive industry are often resolved using embedded control systems. As a result, a modern vehicle can be regarded as a complex mechatronic system. However, control design for such systems, in practice, often comes down to time-consuming online tuning and calibration techniques, rather than a more systematic, model-based control design approach. The main goal of this thesis is to contribute to a corresponding paradigm shift, targeting the use of systematic, model-based control design approaches in practice. This implies the use of control-oriented modeling and the specification of corresponding performance requirements as a basis for the actual controller synthesis. Adopting a systematic, model-based control design approach, as opposed to pragmatic, online tuning and calibration techniques, is a prerequisite for the application of state-of-the-art controller synthesis methods. These methods enable to achieve guarantees regarding robustness, performance, stability, and optimality of the synthesized controller. Furthermore, from a practical point-of-view, it forms a basis for the reduction of tuning and calibration effort via automated controller synthesis, and fulfilling increasingly stringent performance demands. To demonstrate these opportunities, case studies are defined and executed. In all cases, actual implementation is pursued using test vehicles and a hardware-in-the-loop setup. • Case I: Judder-induced oscillations in the driveline are resolved using a robustly stable drive-off controller. The controller prevents the need for re-tuning if the dynamics of the system change due to wear. A hardware-in-the-loop setup, including actual sensor and actuator dynamics, is used for experimental validation. • Case II: A solution for variations in the closed-loop behavior of cruise control functionality is proposed, explicitly taking into account large variations in both the gear ratio and the vehicle loading of heavy duty vehicles. Experimental validation is done on a heavy duty vehicle, a DAF XF105 with and without a fully loaded trailer. • Case III: A systematic approach for the design of an adaptive cruise control is proposed. The resulting parameterized design enables intuitive tuning directly related to comfort and safety of the driving behavior and significantly reduces tuning effort. The design is validated on an Audi S8, performing on-the-road experiments. • Case IV: The design of a cooperative adaptive cruise control is presented, focusing on the feasibility of implementation. Correspondingly, a necessary and sufficient condition for string stability is derived. The design is experimentally tested using two Citroën C4’s, improving traffic throughput with respect to standard adaptive cruise control functionality, while guaranteeing string stability of the traffic flow. The case studies consider representative automotive control problems, in the sense that typical challenges are addressed, being variable operating conditions and global performance qualifiers. Based on the case studies, a generic classification of automotive control problems is derived, distinguishing problems at i) a full-vehicle level, ii) an in-vehicle level, and iii) a component level. The classification facilitates a characterization of automotive control problems on the basis of the required modeling and the specification of corresponding performance requirements. Full-vehicle level functionality focuses on the specification of desired vehicle behavior for the vehicle as a whole. Typically, the required modeling is limited, whereas the translation of global performance qualifiers into control-oriented performance requirements can be difficult. In-vehicle level functionality focuses on actual control of the (complex) vehicle dynamics. The modeling and the specification of performance requirements are typically influenced by a wide variety of operating conditions. Furthermore, the case studies represent practical application examples that are specifically suitable to apply a specific set of state-of-the-art controller synthesis methods, being robust control, model predictive control, and gain scheduling or linear parameter varying control. The case studies show the applicability of these methods in practice. Nevertheless, the theoretical complexity of the methods typically translates into a high computational burden, while insight in the resulting controller decreases, complicating, for example, (online) fine-tuning of the controller. Accordingly, more efficient algorithms and dedicated tools are required to improve practical implementation of controller synthesis methods