A Controls-Oriented Approach For Modeling Professional Drivers During Ultra-High Performance Maneuvers

In the study of vehicle dynamics and controls, modeling ultra-high performance maneuvers (i.e., minimum-time vehicle maneuvering) is a fascinating problem that explores the boundaries of capabilities for a human controlling a machine. Professional human drivers are still considered the benchmark for controlling a vehicle during these limit handling maneuvers. Different drivers possess unique driving styles, i.e. preferences and tendencies in their local decisions and corresponding inputs to the vehicle. These differences in the driving style among professional drivers or sets of drivers are duly considered in the vehicle development process for component selection and system tuning to push the limits of achievable lap times. This work aims to provide a mathematical framework for modeling driving styles of professional drivers that can then be embedded in the vehicle design and development process. This research is conducted in three separate phases. The first part of this work introduces a cascaded optimization structure that is capable of modeling driving style. Model Predictive Control (MPC) provides a natural framework for modeling the human decision process. In this work, the inner loop of the cascaded structure uses an MPC receding horizon control strategy which is tasked with finding the optimal control inputs (steering, brake, throttle, etc.) over each horizon while minimizing a local cost function. Therein, we extend the typical fixed-cost function to be a blended cost capable of optimizing different objectives. Then, an outer loop finds the objective weights used in each MPC control horizon. It is shown that by varying the driver\u27s objective between key horizons, some of the sub-optimality inherent to the MPC process can be alleviated. In the second phase of this work, we explore existing onboard measurements of professional drivers to compare different driving styles. We outline a novel racing line reconstruction technique rooted in optimal control theory to reconstruct the driving lines for different drivers from a limited set of measurements. It is demonstrated that different drivers can achieve nearly identical lap times while adopting different racing lines. In the final phase of this work, we use our racing line technique and our cascaded optimization framework to fit computable models for different drivers. For this, the outer loop of the cascaded optimization finds the set of objective weights used in each local MPC horizon that best matches simulation to onboard measurements. These driver models will then be used to optimize vehicle design parameters to suit each driving style. It will be shown that different driving styles will yield different parameters that optimize the driver/vehicle system

Control and communication systems for automated vehicles cooperation and coordination

Mención Internacional en el título de doctorThe technological advances in the Intelligent Transportation Systems (ITS) are exponentially improving over the last century. The objective is to provide intelligent and innovative services for the different modes of transportation, towards a better, safer, coordinated and smarter transport networks. The Intelligent Transportation Systems (ITS) focus is divided into two main categories; the first is to improve existing components of the transport networks, while the second is to develop intelligent vehicles which facilitate the transportation process. Different research efforts have been exerted to tackle various aspects in the fields of the automated vehicles. Accordingly, this thesis is addressing the problem of multiple automated vehicles cooperation and coordination. At first, 3DCoAutoSim driving simulator was developed in Unity game engine and connected to Robot Operating System (ROS) framework and Simulation of Urban Mobility (SUMO). 3DCoAutoSim is an abbreviation for "3D Simulator for Cooperative Advanced Driver Assistance Systems (ADAS) and Automated Vehicles Simulator". 3DCoAutoSim was tested under different circumstances and conditions, afterward, it was validated through carrying-out several controlled experiments and compare the results against their counter reality experiments. The obtained results showed the efficiency of the simulator to handle different situations, emulating real world vehicles. Next is the development of the iCab platforms, which is an abbreviation for "Intelligent Campus Automobile". The platforms are two electric golf-carts that were modified mechanically, electronically and electrically towards the goal of automated driving. Each iCab was equipped with several on-board embedded computers, perception sensors and auxiliary devices, in order to execute the necessary actions for self-driving. Moreover, the platforms are capable of several Vehicle-to-Everything (V2X) communication schemes, applying three layers of control, utilizing cooperation architecture for platooning, executing localization systems, mapping systems, perception systems, and finally several planning systems. Hundreds of experiments were carried-out for the validation of each system in the iCab platform. Results proved the functionality of the platform to self-drive from one point to another with minimal human intervention.Los avances tecnológicos en Sistemas Inteligentes de Transporte (ITS) han crecido de forma exponencial durante el último siglo. El objetivo de estos avances es el de proveer de sistemas innovadores e inteligentes para ser aplicados a los diferentes medios de transporte, con el fin de conseguir un transporte mas eficiente, seguro, coordinado e inteligente. El foco de los ITS se divide principalmente en dos categorías; la primera es la mejora de los componentes ya existentes en las redes de transporte, mientras que la segunda es la de desarrollar vehículos inteligentes que hagan más fácil y eficiente el transporte. Diferentes esfuerzos de investigación se han llevado a cabo con el fin de solucionar los numerosos aspectos asociados con la conducción autónoma. Esta tesis propone una solución para la cooperación y coordinación de múltiples vehículos. Para ello, en primer lugar se desarrolló un simulador (3DCoAutoSim) de conducción basado en el motor de juegos Unity, conectado al framework Robot Operating System (ROS) y al simulador Simulation of Urban Mobility (SUMO). 3DCoAutoSim ha sido probado en diferentes condiciones y circunstancias, para posteriormente validarlo con resultados a través de varios experimentos reales controlados. Los resultados obtenidos mostraron la eficiencia del simulador para manejar diferentes situaciones, emulando los vehículos en el mundo real. En segundo lugar, se desarrolló la plataforma de investigación Intelligent Campus Automobile (iCab), que consiste en dos carritos eléctricos de golf, que fueron modificados eléctrica, mecánica y electrónicamente para darle capacidades autónomas. Cada iCab se equipó con diferentes computadoras embebidas, sensores de percepción y unidades auxiliares, con la finalidad de transformarlos en vehículos autónomos. Además, se les han dado capacidad de comunicación multimodal (V2X), se les han aplicado tres capas de control, incorporando una arquitectura de cooperación para operación en modo tren, diferentes esquemas de localización, mapeado, percepción y planificación de rutas. Innumerables experimentos han sido realizados para validar cada uno de los diferentes sistemas incorporados. Los resultados prueban la funcionalidad de esta plataforma para realizar conducción autónoma y cooperativa con mínima intervención humana.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Francisco Javier Otamendi Fernández de la Puebla.- Secretario: Hanno Hildmann.- Vocal: Pietro Cerr

Contactless magnetic brake for automotive applications

Road and rail vehicles and aircraft rely mainly or solely on friction brakes. These brakes pose several problems, especially in hybrid vehicles: significant wear, fading, complex and slow actuation, lack of fail-safe features, increased fuel consumption due to power assistance, and requirement for anti-lock controls. To solve these problems, a contactless magnetic brake has been developed. This concept includes a novel flux-shunting structure to control the excitation flux generated by permanent magnets. This brake is wear-free, less-sensitive to temperature than friction brakes, has fast and simple actuation, and has a reduced sensitivity to wheel-lock. The present dissertation includes an introduction to friction braking, a theory of eddy-current braking, analytical and numerical models of the eddy-current brake, its excitation and power generation, record of experimental validation, investigation and simulation of the integration of the brake in conventional and hybrid vehicles

Powertrain Architectures and Technologies for New Emission and Fuel Consumption Standards

New powertrain design is highly influenced by CO2 and pollutant limits defined by legislations, the demand of fuel economy in for real conditions, high performances and acceptable cost. To reach the requirements coming from both end-users and legislations, several powertrain architectures and engine technologies are possible (e.g. SI or CI engines), with many new technologies, new fuels, and different degree of electrification. The benefits and costs given by the possible architectures and technology mix must be accurately evaluated by means of objective procedures and tools in order to choose among the best alternatives. This work presents a basic design methodology and a comparison at concept level of the main powertrain architectures and technologies that are currently being developed, considering technical benefits and their cost effectiveness. The analysis is carried out on the basis of studies from the technical literature, integrating missing data with evaluations performed by means of powertrain-vehicle simplified models, considering the most important powertrain architectures. Technology pathways for passenger cars up to 2025 and beyond have been defined. After that, with support of more detailed models and experimentations, the investigation has been focused on the more promising technologies to improve internal combustion engine, such as: water injection, low temperature combustions and heat recovery systems

Developments in Stochastic Fuel Efficient Cruise Control and Constrained Control with Applications to Aircraft.

This dissertation presents contributions to fuel-efficient control of vehicle speed and constrained control with applications to aircraft. In the first part of this dissertation a stochastic approach to fuel-efficient vehicle speed control is developed. This approach encompasses stochastic modeling of road grade and traffic speed and uses the application of stochastic dynamic programming to generate vehicle speed control policies that are optimized for the trade-off between fuel consumption and travel time. It is shown that the policies lead to the emergence of time-varying vehicle speed patterns, often referred to as pulse and glide (PnG). Through simulations and experiments it is confirmed that these time-varying vehicle speed profiles are more fuel-efficient than driving at a comparable constant speed. A practical implementation strategy of these patterns is then developed and demonstrated. Also, several additional contributions are made to approaches for stochastic modeling of road grade and vehicle speed that include the use of Kullback-Liebler divergence and divergence rate and a stochastic jump-like model for the behavior of the road grade. In the second part of the dissertation, contributions to constrained control with applications to aircraft are described. Recoverable sets and integral safe sets of initial states of constrained closed-loop systems are introduced first and computational procedures of such sets based on linear discrete-time models are given. An approach to constrained flight planning based on chaining recoverable sets or integral safe sets is described and illustrated with a simulation example. Finally, two control schemes that exploit integral safe sets are proposed. The first scheme, referred to as the controller state governor (CSG), resets the controller state (typically an integrator) to enforce the constraints and enlarge the set of plant states that can be recovered without constraint violation. The second scheme, referred to as the controller state and reference governor (CSRG), combines the controller state governor with the reference governor control architecture and provides the capability of simultaneously modifying the reference command and the controller state to enforce the constraints. Theoretical results that characterize the response properties of both schemes are presented. Examples are reported that illustrate the operation of these schemes.PhDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111399/1/kevinmcd_1.pd

Nonlinear Model Predictive Control Reduction Strategies for Real-time Optimal Control

This thesis presents a variety of strategies to accelerate the turnaround times (TATs) of nonlinear and hybrid model predictive controllers (MPCs). These strategies are unified by the themes of symbolic computing, nonlinear model reduction and automotive control. The first contribution of this thesis is a new MPC problem formulation, called symbolic single shooting (symSS), that leverages the power of symbolic computing to generate an optimization problem of minimal dimension. This formulation is counter to the recent trend of introducing and exploiting sparsity of the MPC optimization problem for tailored solvers to exploit. We make use of this formulation widely in this thesis. The second contribution of this thesis is a novel application of proper orthogonal decomposition (POD) to MPC. In this strategy we construct a dimensionally-reduced optimization problem by restricting the problem Lagrangian to a subspace. This subspace is found by running simulations offline from which we extract the important solution features. Using this restricted Lagrangian we are able to reduce the problem dimension dramatically, thus simplifying the linear solve. This leads to TAT accelerations of more than two times with minimal controller degradation. The third contribution of this thesis is an informed move blocking strategy. This strategy exploits the features extracted in the restricted Lagrangian subspace to derive a sequence of increasingly blocked move blocking strategies. These move blocking strategies can then be used to reduce the dimension of the optimization problem in a sparse manner, leading to even greater acceleration of the controller TAT . The fourth contribution of this thesis is a new quasi-Newton method for MPC. This method utilizes ideas similar to singular perturbation-based model reduction to truncate the expression for the problem Hessian at the symbolic level. For nonlinear systems with a modest Lipschitz constant, we can identify the timestep as a `small' parameter about which we can do a perturbative expansion of the Lagrangian and its derivatives. Truncating to first order in the timestep, we are able to find a good approximation of the Hessian leading to TAT acceleration. The fifth contribution of this thesis is controller integration strategy based on nested MPCs. Using the symSS formulation we can construct an explicit model of a controlled plant that includes the full model as well as the MPC's action. This form of the controlled plant model allows us to generate exact derivatives so that fast solvers can be used for real time application. We focus here on the problem of planning and motion control integration for autonomous vehicles but this strategy can be extended for other problems that require accurate models of a controlled plant. The sixth contribution of this thesis is a strategy to handle integer controls in MPC based on a few reasonable assumptions: our predictions over the horizon are almost perfect and the future is inevitable. These assumptions enforce a degree of continuity, in the integer controls, between solutions over different timesteps that allow us to mitigate chatter and enforce a hard upper bound on solution complexity. This strategy constrains the integer solution of one timestep to be related to that of the previous timestep. Our results show that this strategy provides acceptable control performance while achieving TATs that are orders of magnitude smaller than those for conventional MINLP-based methods, thereby opening the door to new real-time applications of hybrid MPC

Systems modelling and simulation in the product development process for automotive powertrains : executive summary

This submission is a summary of the ten submissions that form the Engineering Doctorate Portfolio. The aim of the portfolio is to demonstrate the benefit of applying systems modelling and simulation in a modified powertrain product development process. A description is given of the competitive pressures that are faced by motor manufacturers in the global automotive business environment. Competitive pressures include a requirement for reduced time to market, exacting product quality standards, manufacturing over-capacity that increases fixed costs and compromises profit margins, and legislation that is increasingly difficult to meet. High-level strategic responses that are being made by manufacturers to these pressures are presented. Each strategic response requires organisational changes and improved approaches to the way in which day-to-day business is conducted. Computer Aided Engineering (CAE) is presented as an approach that can help to improve the competitiveness of motor manufacturers by reducing product development time and the level of hardware prototyping that is required. An investigation in five engineering companies yielded a number of observations about the use of CAE and its integration into product development. Best practice in the implementation of CAE in the product development process is defined. The use of CAE by a leading motor manufacturer in powertrain development is compared with the best practice model, and it is identified that there is a lack of coherence in the application of CAE. It is used to tackle specific problems but the use of CAE is not integrated into the product development process. More importantly, it was found that there is limited application of systems modelling and simulation, which is a critical technique for the effective integration of vehicle systems and the development of on-board vehicle control systems. Before systems modelling and simulation can be applied III powertrain development, an appropriate set of tools and associated modelling architecture must be determined. An appraisal of a range of different tools is undertaken, each tool being appraised against a set of criteria. A combination of DymolaIModelica and MATLAB/Simulink tools is recommended as the optimum solution. DymolaIModelica models of the vehicle plant should be embedded into Simulink models that also contain controller and driver models. MATLAB should be used as the numerical engine and for the creation of user environments. Transmission calibration is selected as a suitable pilot example for applying systems modelling and simulation in powertrain development. Best practice in CAE implementation and the systems modelling and simulation architecture are validated using this example. Simulation models of vehicles equipped with CVT and discrete ratio automatic transmissions are presented. A full description of the operation of the transmission system, of the simulation model itself, and of the validation of the model is presented in each case. The potential benefit of the CVT model in transmission calibration is demonstrated. A Transmission Calibration Simulation Tool (TCST) is described within which the discrete ratio simulation model is encapsulated. The TCST includes a user environment in which the simulation model can be parameterised, a variety of simulation runs can be specified, and simulation results are processed. Development of the TCST requires an objective measure of driveability effects that are influenced by the transmission shift schedule. A method for objective assessment of driveability is developed, correlated, and implemented as an integral part of the TCST. This element of the TCST allows trade-off exercises to be conducted between fuel economy and driveability. The development of a transmission calibration based on experimental testing is compared with a similar exercise based on simulation testing. This study shows that, if the TCST is properly integrated into the transmission calibration process, the vehicle test time taken to optimise the calibration for fuel economy could be reduced by six weeks, and a week of calibrator time could be saved. Thus, the aim of the submission is fulfilled, since the benefit of applying systems modelling and simulation in the powertrain development process has been demonstrated. It is concluded that a consistent approach is required for effectively integrating systems modelling and simulation into the product development process. A model is proposed that clarifies how this can be achieved at a local level. It is proposed that in the future, the model is applied whenever systems modelling and simulation is introduced into a powertrain department