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The abstracts for some of the presentations can be viewed by selecting the titles below. 

AVECS 2017 abstracts

  • Connected Vehicle Technologies: Integrated Wireless Sensor Research at UOIT

    Presenter: Langis Roy, PhD, Dean, School of Graduate and Postdoctoral Studies, University of Ontario Institute of Technology

     The connected vehicle is already a mainstream reality; however, new levels of connectivity and intelligence are acutely required. 'Vehicle-to-everything' communication and 'always-on' sensing are two particularly important areas of development. This presentation will describe several advanced device/component technologies currently being pursued at the University of Ontario Institute of Technology to enable integrated wireless sensors for automotive applications. Emphasis will be placed on novel low-cost environmental sensors, agile radio-communicating devices, flexible/conformally-mounted antennas, self-powering and advanced device integration approaches. Recent examples of system-on-chip and system-on-package solutions will be presented.


  • Automotive PEM fuel cell system evaluation, testing and validation technology during integration

    Presenter: Zhang Xifeng, Lecturer, School of Automotive Studies, Tongji University

    Abstract: Design method of standard testing cell for automotive PEM fuel cell system was proposed. According to PEMFCs comprehensive evaluation requirement, the  requisite facilities of the testing platform were presented. Firstly, comparison between the ICE testing cell and fuel cell engine testing cell was carried out, and similar facilities were adopted while different facilities was designed. Secondly, a thermal dynamic model was setup and a “5-4-1(4-1)” rule of heat flow was proposed based on the simulation result. Third, ventilation and air treatment were designed in detail. Finally, a distributed test platform was setup with the NI CompactRIO and PXIe based hardware, which performed as the signal processor, a virtual instrument based software architecture of the test platform was adopted. The test platform was proved to have the ability to measure the metrics of PEMFCs performance.

  • Simultaneous optimization of powertrain and on-board applicable energy management strategies for hybrid fuel cell vehicles

    Presenter: Marco Sorrentino, PhD, Assistant Professor of Energy Conversion Systems, University of Salerno.

    Abstract: The present work proposes a computational tool that integrates the definition of efficient energy management strategies with model-based optimal design of a hybrid fuel cell hybrid powertrain destined to automotive applications. Particularly, suited normalization and denormalization techniques are proposed, so as to adapt optimized control rules to a number of FCHEV powertrains, ranging from low to high degree of hybridization. Afterwards, the outcomes, as resulted from the application of these techniques, have been exploited to perform a model-based scenario analysis aimed at optimally designing a fuel cell hybrid electric vehicle (FCHEV). The optimization algorithm was conceived in such a way as to make it possible, for an assigned route, solving a constrained optimization problem, in which are determined the optimum values of the fuel cell system (FCS) nominal power and battery specific energy, with the final aim of maximizing vehicle Fuel Economy (objective function). The assumed constraints include, beyond the explorable FCS and battery size ranges, the maximum time for after-trip battery recharging, thus allowing diversifying the control objectives, as well as choosing the best energy management strategy for the entire hybrid powertrain.    

  • Battery Pack Thermal Modeling for the Chevrolet Volt under Dynamic Operating Conditions

    Presenter: Greg Rohrauer, PhD, Associate Professor, Faculty of Engineering and Applied Science, University of Ontario Institute of Technology

    Abstract: The development of a dynamic thermal battery model for the Chevy Volt is realized. A thermal equivalent circuit network is created which aims to capture and understand the heat propagation from the cells through the entire pack and to the environment using a production vehicle battery pack for model validation. Focus is placed on the influence of packaging components external to the cell modules, and on the pack’s response to ambient environmental influences. The thermal network model representing the pack was refined experimentally using heat flux and temperature measurements taken over a series of more than 100 laboratory test runs on a production vehicle battery pack.

    The initial model representing lab conditions produced simulation results with very good accuracy, comparable to the level of signal noise itself. The verified and calibrated lab model was then modified to match the environment of the real vehicle, taking into consideration engine bay temperature, chassis temperature, underbody convection, and road radiation. This full thermal model was further checked using road test data, and still reproduced temperature and heat flow with accuracy comparable to the initial lab test runs. The inclusion of production hardware and the liquid battery thermal management system components into the model considers physical and geometric properties to calculate thermal resistances of components (conduction, convection and radiation) along with their associated heat capacity. Various heat sources/sinks comprise the remaining model elements.

    Analog equivalent circuit simulations using PSpice are compared with experimental results to validate internal temperature nodes and heat rates measured through various elements. The experimental results are then employed to further refine the model, and road data is used for a final comparison. Agreement with experimental results indicates the proposed method allows for a comprehensive real-time battery pack analysis at little computational expense. The thermal network representation achieved is employed in conjunction with a separate powertrain simulation model 'Autonomie' to perform a complete vehicle dynamic analysis regarding battery thermal effects through a wide range of drive profiles combined with environmental exposure conditions.

    Elevated road and ambient conditions through a variety of stationary conditions and drive cycles are simulated along with diurnal effects, all being translated into cell temperatures. Typical daily driving schedules are simulated and examined to gain insight upon the parameters ultimately controlling the design.

  • Brake Rotor Design Utilizing Advanced Topology Optimization Methods

    Presenter: Davin Jankovics, Graduate Student, Mechanical Engineering, Faculty of Engineering and Applied Science, University of Ontario Institute of Technology

    Abstract: Weight is one of the most important design variables in the automotive industry. As emission regulations become more stringent and the push for more economical and efficient cars becomes stronger, the optimization of vehicles becomes increasingly necessary. Combined with increasingly prevalent high-power computing, advanced optimization techniques are becoming essential to the design process. The development of racing cars is one area in the automotive industry where this technology is rapidly being adopted. A small reduction in weight directly influences how successful the vehicle will be. For this paper, a case study is performed on the effects of advanced topology optimization on the brake rotors of a Formula SAE (Society of Automotive Engineers) Electric car. Using various topology optimization methods and computer vision techniques, the rotor’s thermal dissipation and mechanical stresses are taken as the constraining variables, with the ultimate goal of reducing mass. When compared with a traditionally designed rotor, significant weight reduction is apparent while still keeping similar physical properties.

  • Enhancing lateral stability of car-trailer systems using model reference adaptive control

    Presenter: Smitha Vempaty, PhD student, Department of Automotive, Mechanical and Manufacturing Engineering, Faculty of Engineering and Applied Science, University of Ontario Institute of Technology

    Abstract: This paper presents a Model Reference Adaptive Controller (MRAC) for the active steering of a trailer to improve the lateral stability of car-trailer (CT) systems. A three degrees-of-freedom (DOF) linear yaw-plane CT model is developed as the reference model. The yaw rate of the leading and the trailing units of the reference model are tracked to control and stabilize a non-linear CT model. The Lyapunov-stability-based MRAC technique is employed to handle the dynamics of the CT system. The model parameters and operating conditions of the vehicle system are assumed to be constant while designing the controller. The effectiveness of the MRAC controller is demonstrated using numerical simulations of the non-linear CT model under a single lane-change maneuver.

  • Nonlinear Stability Analysis Using Lyapunov Stability Theory for Car-Trailer Systems

    Presenter: Tao Sun, PhD student, Department of Automotive, Mechanical and Manufacturing Engineering, Faculty of Engineering and Applied Science, University of Ontario Institute of Technology

    Abstract: This paper presents a bifurcation analysis for car-trailer lateral stability considering the variation of forward vehicle velocity. As an important aspect in car-trailer dynamics, the lateral stability has a strong influence on the overall vehicle safety. To increase car-trailer safety, it is vital to estimate the lateral stability region. With respect to single-unit vehicles, such as cars and trucks, car-trailer systems (CTSs) exhibit unique dynamic features, including unstable motion modes, namely, jack-knifing, trailer sway and rollover. Thus, we perform a sensitivity analysis using the Lyapunov stability theory to evaluate the nonlinear stability features of a CTS. To this end, a six degrees of freedom (DOF) nonlinear car-trailer model is generated, which is a non-autonomous system at different forward velocity. The nonlinear lateral stability analysis paves the road for developing active safety systems for CTSs.

  • Identifying Driver Skills based on Driver Models for Multi-Trailer Heavy Vehicles

    Presenter: Jesse Brown, master's student, Automotive Engineering, Faculty of Engineering and Applied Science, University of Ontario Institute of Technology

    Abstract: This paper presents a driving skill analysis for comparing different drivers in various operating conditions. The analysis demonstrates how driver model variables, e.g., preview time and transport delay, effect path following and dynamic behaviors of various heavy vehicle combinations. Three types of heavy vehicles are evaluated: a tractor only, tractor/semitrailer and multi-trailer B-train, in a closed-loop single lane-change maneuver. To assess the driving performance, two measures—path following score (PFS) and combined stability scores (CSC)—are introduced. The result displays driver ability in terms of a visualized spectrum, highlighting the features of driving behaviour while driving different types of heavy vehicles.

  • Fault diagnosis techniques for Active Trailer Steering Systems of Multi-Trailer Articulated Heavy Vehicles

    Presenter: Saurabh Kapoor, master’s student, Department of Automotive, Mechanical and Manufacturing Engineering, Faculty of Engineering and Applied Science, University of Ontario Institute of Technology

    Abstract: Faults in a controlled plant often deteriorate the system performance. In severe cases, faults pose a risk of component damage, plant shutdown or even personnel safety. Fault tolerance aims at preventing the escalation of rectifiable faults to serious failure. It combines fault diagnosis with reconfiguration methods to manage faults intelligently. This research presents a Fault Detection and Diagnosis (FDD) method for Active Trailer Steering (ATS) systems of Multi-Trailer Articulated Heavy Vehicles (MTAHVs). An observer-based FDD system is developed. To enhance the vehicle dynamics, a H∞ controlled hydraulic ATS system is designed. Fault diagnosis techniques, e.g., Kalman Filter are applied, and dynamic performance under the high-speed single lane-change (SLC) and double lane-change (DLC) maneuvers is investigated. TruckSim software package is used to simulate the vehicle performance, and fault scenarios, e.g., actuator malfunction and sensor failure, are explored.

  • Robust control techniques of Active Trailer Steering systems for Long Combination Vehicles

    Presenter: Tushita Sikder, Master of Science (Automotive Engineering), class of 2017, University of Ontario Institute of Technology

    Abstract: The growth in freightage and the ever-increasing traffic congestion has aided long combination vehicles (LCVs) to emerge as an economical solution for freight transport compared to single unit vehicle. They can not only reduce traffic congestion problems but also can significantly improve fuel economy and reduce greenhouse emissions. Despite their numerous merits, LCVs experiences certain stability challenges at high speeds and exhibit inferior maneuverability at low speeds. This has escalated strong concerns regarding the safety of such vehicles. Active Safety Systems (ASS), e.g. Active Trailer Steering (ATS), have been explored to overcome these challenges. Most of the research conducted on ATS has been focused on using linear quadratic regulator (LQR) technique. Although the LQR technique exhibit pleasing results, it alone cannot effectively control the system in presence of disturbances such as sensor noise, parametric uncertainties and un-modelled dynamics. These disturbances often leads to system failures. This encourages a need of control strategy, which is both robust and adaptable. This research focuses on developing robust control techniques for safety systems for a B-train LCV. To augment the robustness of the existing LQR controller, a Kalman filter (KF) is added, as a state estimator. KF assists LQR in predicting the states in the presence of the disturbances. Another robust technique, 𝜇 synthesis, is investigated. This elaborative research aims on illustrating a comparison between the different control strategies used for implementing ATS in LCVs. The research inclines toward achieving lateral stability of the LCVs at high speeds.

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