Download or read book Vehicle Fuel Consumption Optimization Using Model Predictive Control Based on V2V Communication written by Junbo Jing and published by . This book was released on 2014 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: As people are working hard on improving vehicle's fuel economy, a large portion of fuel consumption in everyday driving is wasted by vehicle driver's inexperienced operations and inefficient judgments. This thesis proposes a system that optimizes the vehicle's fuel consumption in automated car-following scenarios. The system is designed able to work in the initial stage of implementing Vehicle-to-Vehicle (V2V) communications.

Download or read book Predictive Energy Optimization in Connected and Automated Vehicles Using Approximate Dynamic Programming written by Shreshta Rajakumar Deshpande and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Global CO2 emissions regulations, in conjunction with increasing customer demands are requiring significant improvements in vehicle energy (or fuel) efficiency. In this drive to reduce fuel consumption, improvements in the powertrain (or propulsion system) continue to be a major area of focus, particularly shifting to higher levels of electrification. A next step in the evolution of improving fuel efficiency is to have the propulsion system controller make use of vehicle-level information. In this context, Connected and Automated Vehicle (CAV) technologies offer the potential for enhancing the vehicle fuel efficiency as well as improving vehicle safety and comfort by leveraging information from advanced mapping and location, and Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication. The focus of this thesis is to develop Dynamic Programming (DP) and Approximate Dynamic Programming (ADP) based approaches that combine the energy-saving potentials of powertrain electrification and CAV technologies, and further compound them. In this work, an ADP-based scheme is used to jointly optimize the vehicle velocity and energy management strategy of an electrified CAV over real-world driving routes. This predictive controls framework uses preview information from the route and environment to achieve significant fuel efficiency improvements even in the presence of variabilities (such as driver aggressiveness and varying traffic signal information). The controller was then implemented and tested in a demonstration vehicle at a proving ground facility over reconstructed route scenarios. Further, this thesis explores approaches to reducing the computational complexity of optimization methods based on Dynamic Programming, which can restrict its use in many real-time applications. To this end, two sub-optimal methodologies are proposed. One of them, the integrated DP-ECMS (Dynamic Programming-Equivalent Consumption Minimization Strategy) method embeds a heuristic strategy within the DP framework. In doing so, the resulting implementation is only marginally sub-optimal compared to the (original) DP, while mitigating the curse of dimensionality. The second method proposed to reduce computation time is the WASP (Warm Start Dynamic Programming) algorithm. Specifically, the solution to a perturbed receding horizon optimal control problem was computed in an approximately optimal manner, by making use of the value function and other properties of the original (unperturbed) DP solution. Its efficacy is demonstrated through application in simplified dynamic optimization problems.

Download or read book Applications of Model Predictive Control to Vehicle Dynamics for Active Safety and Stability written by Craig Earl Beal and published by Stanford University. This book was released on 2011 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Each year in the United States, thousands of lives are lost as a result of loss of control crashes. Production driver assistance systems such as electronic stability control (ESC) have been shown to be highly effective in preventing many of these automotive crashes, yet these systems rely on a sensor suite that yields limited information about the road conditions and vehicle motion. Furthermore, ESC systems rely on gains and thresholds that are tuned to yield good performance without feeling overly restrictive to the driver. This dissertation presents an alternative approach to providing stabilization assistance to the driver which leverages additional information about the vehicle and road that may be obtained with advanced estimation techniques. This new approach is based on well-known and robust vehicle models and utilizes phase plane analysis techniques to describe the limits of stable vehicle handling, alleviating the need for hand tuning of gains and thresholds. The resulting state space within the computed handling boundaries is referred to as a safe handling envelope. In addition to the boundaries being straightforward to calculate, this approach has the benefit of offering a way for the designer of the system to directly adjust the controller to accomodate the preferences of different drivers. A model predictive control structure capable of keeping the vehicle within the safe handling boundaries is the final component of the envelope control system. This dissertation presents the design of a controller that is capable of smoothly and progressively augmenting the driver steering input to enforce the boundaries of the envelope. The model predictive control formulation provides a method for making trade-offs between enforcing the boundaries of the envelope, minimizing disruptive interventions, and tracking the driver's intended trajectory. Experiments with a steer-by-wire test vehicle demonstrate that the model predictive envelope control system is capable of operating in conjunction with a human driver to prevent loss of control of the vehicle while yielding a predictable vehicle trajectory. These experiments considered both the ideal case of state information from a GPS/INS system and an a priori friction estimate as well as a real-world implementation estimating the vehicle states and friction coefficient from steering effort and inertial sensors. Results from the experiments demonstrated a controller that is tolerant of vehicle and tire parameterization errors and works well over a wide range of conditions. When real time sensing of the states and friction properties is enabled, the results show that coupling of the controller and estimator is possible and the model predictive control structure provides a mechanism for minimizing undesirable coupled dynamics through tuning of intuitive controller parameters. The model predictive control structure presented in this dissertation may also be considered as a general framework for vehicle control in conjunction with a human driver. The structure utilized for envelope control may also be used to restrict other vehicle states for safety and stability. Results are presented in this dissertation to show that a model predictive controller can coordinate a secondary actuator to alter the planar states and reduce the energy transferred into the roll modes of the vehicle. The systematic approach to vehicle stabilization presented in this dissertation has the potential to improve the design methodology for future systems and form the basis for the inclusion of more advanced functions as sensing and computing capabilities improve. The envelope control system presented here offers the opportunity to advance the state of the art in stabilization assistance and provides a way to help drivers of all skill levels maintain control of their vehicle.

Download or read book Hybrid Electric Vehicles written by Simona Onori and published by Springer. This book was released on 2015-12-16 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: This SpringerBrief deals with the control and optimization problem in hybrid electric vehicles. Given that there are two (or more) energy sources (i.e., battery and fuel) in hybrid vehicles, it shows the reader how to implement an energy-management strategy that decides how much of the vehicle’s power is provided by each source instant by instant. Hybrid Electric Vehicles: •introduces methods for modeling energy flow in hybrid electric vehicles; •presents a standard mathematical formulation of the optimal control problem; •discusses different optimization and control strategies for energy management, integrating the most recent research results; and •carries out an overall comparison of the different control strategies presented. Chapter by chapter, a case study is thoroughly developed, providing illustrative numerical examples that show the basic principles applied to real-world situations. The brief is intended as a straightforward tool for learning quickly about state-of-the-art energy-management strategies. It is particularly well-suited to the needs of graduate students and engineers already familiar with the basics of hybrid vehicles but who wish to learn more about their control strategies.

Download or read book Model Predictive Control System Design and Implementation Using MATLAB written by Liuping Wang and published by Springer Science & Business Media. This book was released on 2009-02-14 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Predictive Control System Design and Implementation Using MATLAB® proposes methods for design and implementation of MPC systems using basis functions that confer the following advantages: - continuous- and discrete-time MPC problems solved in similar design frameworks; - a parsimonious parametric representation of the control trajectory gives rise to computationally efficient algorithms and better on-line performance; and - a more general discrete-time representation of MPC design that becomes identical to the traditional approach for an appropriate choice of parameters. After the theoretical presentation, coverage is given to three industrial applications. The subject of quadratic programming, often associated with the core optimization algorithms of MPC is also introduced and explained. The technical contents of this book is mainly based on advances in MPC using state-space models and basis functions. This volume includes numerous analytical examples and problems and MATLAB® programs and exercises.

Download or read book Use of Connected Vehicle Technology for Improving Fuel Economy and Driveability of Autonomous Vehicles written by Santhosh Tamilarasan and published by . This book was released on 2019 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: Connected vehicles promise to increase transportation options and reduce travel times while improving the safety of road users. Convoying/platooning are the common use case of connected vehicles technology and the driveability performance impact of such convoy has never been researched before. The vehicles when following each other in a convoy, using adaptive cruise control (ACC), is augmented by the lead vehicle information (vehicle acceleration) through the vehicle to vehicle communication as a feedforward control is called Cooperative Adaptive Cruise Control (CACC). This dissertation analyses the impact of the desired velocity profile on the driveability characteristics of a convoy of vehicles. In order to assess the driveability performance, a framework consisting of various metrics has been developed. The parameter space robust control methodology has been used to design the controller that improves the convoy's driveability and the performance is compared to the convoy that is being tuned for maintaining the time gap. These simulation results were verified in a real-time setting using a Hardware-in-the-Loop (HIL) setup using a CARSIM high-fidelity car model. With the use of the V2X technology, the fuel economy of the connected vehicle can be improved and it is called Eco-Driving. This dissertation proposes a framework for Eco-driving that is comprised of Eco-Cruise, Greenwave algorithm, and Eco-CACC. The Eco-Cruise is the algorithm which calculates the optimal velocity profile based on the route information such as speed limit, stop sign and traffic sign location and the vehicle powertrain model. A Dynamic programming based algorithm which minimizes the fuel economy is developed. The Eco-Cruise algorithm stops at all the stop signs and traffic light (assuming red light) optimally. Driving scenario has a very big impact on the Eco-cruise algorithm, and a new methodology has been proposed in this dissertation, that formulates a metric based route selection that evaluates the potential of the Eco-cruise in the different driving scenario. When the vehicle approaches the traffic light intersection, V2X technology is used, where the Signal Phase and Timing information (SPaT) information from the traffic light is communicated via DSRC communication modem to the vehicle. The green wave algorithm utilizes the SPaT information to calculate a velocity profile that allows the vehicle to pass in green and overrides the Eco-cruise velocity profile. Although the current greenwave algorithms save fuel by not stopping at the traffic light, the explicit fuel economy optimization is not considered in the velocity profile generation. The dissertation uses an MPC methodology with non-linear optimization that generates the velocity profile that minimizes the fuel economy and satisfies the constraints and allows the vehicle to pass through greenlight. In case of the traffic situation, where there is a lead vehicle, the maximum vehicle velocity of the host vehicle is limited by the speed of the lead vehicle, and may not follow the Eco-Cruise vehicle speed. In such cases of car-following mode, the host vehicle follows the lead vehicle optimally by using the V2V communication, by varying the gap to save fuel economy. An MPC based controller has been designed for this algorithm. Thus this dissertation presents the optimal control algorithm that uses the connected vehicle technology that achieves improvement in driveability and fuel economy

Download or read book Handbook of Model Predictive Control written by Saša V. Raković and published by Springer. This book was released on 2018-09-01 with total page 693 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent developments in model-predictive control promise remarkable opportunities for designing multi-input, multi-output control systems and improving the control of single-input, single-output systems. This volume provides a definitive survey of the latest model-predictive control methods available to engineers and scientists today. The initial set of chapters present various methods for managing uncertainty in systems, including stochastic model-predictive control. With the advent of affordable and fast computation, control engineers now need to think about using “computationally intensive controls,” so the second part of this book addresses the solution of optimization problems in “real” time for model-predictive control. The theory and applications of control theory often influence each other, so the last section of Handbook of Model Predictive Control rounds out the book with representative applications to automobiles, healthcare, robotics, and finance. The chapters in this volume will be useful to working engineers, scientists, and mathematicians, as well as students and faculty interested in the progression of control theory. Future developments in MPC will no doubt build from concepts demonstrated in this book and anyone with an interest in MPC will find fruitful information and suggestions for additional reading.

Download or read book Vehicle Propulsion Systems written by Lino Guzzella and published by Springer Science & Business Media. This book was released on 2005-12-01 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book the longitudinal behavior of road vehicles is analyzed. The main emphasis is on the analysis and minimization of the fuel and energy consumption. Most approaches to this problem enhance the complexity of the vehicle system by adding components such as electrical motors or storage devices. Such a complex system can only be designed by means of mathematical models. This text gives an introduction to the modeling and optimization problems typically encountered when designing new propulsion systems for passenger cars. It is intended for persons interested in the analysis and optimization of classical and novel vehicle propulsion systems. Its focus lies on the control-oriented mathematical description of the physical processes and on the model-based optimization of the system structure and of the supervisory control algorithms. This text has evolved from a lecture series at ETH Zurich. Prerequisites are general engineering topics and a first course in optimal control theory.

Download or read book Optimization and Optimal Control in Automotive Systems written by Harald Waschl and published by Springer. This book was released on 2014-03-20 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book demonstrates the use of the optimization techniques that are becoming essential to meet the increasing stringency and variety of requirements for automotive systems. It shows the reader how to move away from earlier approaches, based on some degree of heuristics, to the use of more and more common systematic methods. Even systematic methods can be developed and applied in a large number of forms so the text collects contributions from across the theory, methods and real-world automotive applications of optimization. Greater fuel economy, significant reductions in permissible emissions, new drivability requirements and the generally increasing complexity of automotive systems are among the criteria that the contributing authors set themselves to meet. In many cases multiple and often conflicting requirements give rise to multi-objective constrained optimization problems which are also considered. Some of these problems fall into the domain of the traditional multi-disciplinary optimization applied to system, sub-system or component design parameters and is performed based on system models; others require applications of optimization directly to experimental systems to determine either optimal calibration or the optimal control trajectory/control law. Optimization and Optimal Control in Automotive Systems reflects the state-of-the-art in and promotes a comprehensive approach to optimization in automotive systems by addressing its different facets, by discussing basic methods and showing practical approaches and specific applications of optimization to design and control problems for automotive systems. The book will be of interest both to academic researchers, either studying optimization or who have links with the automotive industry and to industrially-based engineers and automotive designers.

Download or read book Comparison of Opitimal Energy Management Strategies Using Dynamic Programming Model Predictive Control and Constant Velocity Pattern written by Amol Arvind Patil and published by . This book was released on 2020 with total page 67 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the recent advancements in autonomous vehicle technology, future vehicle velocity predictions are becoming more robust which allows fuel economy (FE) improvements in hybrid electric vehicles through optimal energy management strategies (EMS). A real-world highway drive cycle (DC) and a controls-oriented 2017 Toyota Prius Prime model are used to study potential FE improvements. We proposed three important metrics for comparison: (1) perfect full drive cycle prediction using dynamic programming, (2) 10-second prediction horizon model predictive control (MPC), and (3) 10-second constant velocity prediction. These different velocity predictions are put into an optimal EMS derivation algorithm to derive optimal engine torque and engine speed. The results show that the constant velocity prediction algorithm outperformed the baseline control strategy but underperformed the MPC strategy with an average 1.58% and 2.45% of FE improvement with highway and city-highway DC. Also, using a 10-second prediction window MPC strategy provided FE improvement results close to the full drive cycle prediction case. MPC has the potential to achieve 60%-65% and 70% - 80% of global FE improvement over highway and city-highway DC respectively

Download or read book The Proceedings of the 5th International Conference on Energy Storage and Intelligent Vehicles ICEIV 2022 written by Fengchun Sun and published by Springer Nature. This book was released on 2023-05-10 with total page 1344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes original, peer-reviewed research papers from the 5th International Conference on Energy Storage and Intelligent Vehicles (ICEIV 2022), held online, from December 3 to December 4, 2022. The topics covered include but are not limited to energy storage, power and energy systems, electrified/intelligent transportation, batteries and management, and power electronics. The papers share the latest findings in energy storage and intelligent vehicles, making the book a valuable asset for researchers, engineers, university students, etc.

Download or read book Validating and Refining a Model Predictive Control System to Improve Vehicle Fuel Economy written by Aaron C. Arizpe and published by . This book was released on 2009 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Proceedings of 2021 Chinese Intelligent Systems Conference written by Yingmin Jia and published by Springer Nature. This book was released on 2021-10-06 with total page 866 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 17th Chinese Intelligent Systems Conference, held in Fuzhou, China, on Oct 16-17, 2021. It focuses on new theoretical results and techniques in the field of intelligent systems and control. This is achieved by providing in-depth study on a number of major topics such as Multi-Agent Systems, Complex Networks, Intelligent Robots, Complex System Theory and Swarm Behavior, Event-Triggered Control and Data-Driven Control, Robust and Adaptive Control, Big Data and Brain Science, Process Control, Intelligent Sensor and Detection Technology, Deep learning and Learning Control Guidance, Navigation and Control of Flight Vehicles and so on. The book is particularly suited for readers who are interested in learning intelligent system and control and artificial intelligence. The book can benefit researchers, engineers, and graduate students.

Download or read book Look ahead Information Based Optimization Strategy for Hybrid Electric Vehicles written by Mohammad Alzorgan and published by . This book was released on 2016 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: The environmental impact of the fossil fuels has increased tremendously in the last decade. This impact is one of the most contributing factors of global warming. This research aims to reduce the amount of fuel consumed by vehicles through optimizing the control scheme for the future route information. Taking advantage of more degrees of freedom available within PHEV, HEV, and FCHEV energy management allows more margin to maximize efficiency in the propulsion systems. The application focuses on reducing the energy consumption in vehicles by acquiring information about the road grade. Road elevations are obtained by use of Geographic Information System (GIS) maps to optimize the controller. The optimization is then reflected on the powertrain of the vehicle. The approach uses a Model Predictive Control (MPC) algorithm that allows the energy management strategy to leverage road grade to prepare the vehicle for minimizing energy consumption during an uphill and potential energy harvesting during a downhill. The control algorithm will predict future energy/power requirements of the vehicle and optimize the performance by instructing the power split between the internal combustion engine (ICE) and the electric-drive system. Allowing for more efficient operation and higher performance of the PHEV, and HEV. Implementation of different strategies, such as MPC and Dynamic Programming (DP), is considered for optimizing energy management systems. These strategies are utilized to have a low processing time. This approach allows the optimization to be integrated with ADAS applications, using current technology for implementable real time applications. The Thesis presents multiple control strategies designed, implemented, and tested using real-world road elevation data from three different routes. Initial simulation based results show significant energy savings. The savings range between 11.84% and 25.5% for both Rule Based (RB) and DP strategies on the real world tested routes. Future work will take advantage of vehicle connectivity and ADAS systems to utilize Vehicle to Vehicle (V2V), Vehicle to Infrastructure (V2I), traffic information, and sensor fusion to further optimize the PHEV and HEV toward more energy efficient operation.

Download or read book Autonomous Ground Vehicles written by Ümit Özgüner and published by Artech House. This book was released on 2011 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the near future, we will witness vehicles with the ability to provide drivers with several advanced safety and performance assistance features. Autonomous technology in ground vehicles will afford us capabilities like intersection collision warning, lane change warning, backup parking, parallel parking aids, and bus precision parking. Providing you with a practical understanding of this technology area, this innovative resource focuses on basic autonomous control and feedback for stopping and steering ground vehicles.Covering sensors, estimation, and sensor fusion to percept the vehicle motion and surrounding objects, this unique book explains the key aspects that makes autonomous vehicle behavior possible. Moreover, you find detailed examples of fusion and Kalman filtering. From maps, path planning, and obstacle avoidance scenarios...to cooperative mobility among autonomous vehicles, vehicle-to-vehicle communication, and vehicle-to-infrastructure communication, this forward-looking book presents the most critical topics in the field today.

Download or read book Practical Business Analytics Using SAS written by Shailendra Kadre and published by Apress. This book was released on 2015-02-07 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Business Analytics Using SAS: A Hands-on Guide shows SAS users and businesspeople how to analyze data effectively in real-life business scenarios. The book begins with an introduction to analytics, analytical tools, and SAS programming. The authors—both SAS, statistics, analytics, and big data experts—first show how SAS is used in business, and then how to get started programming in SAS by importing data and learning how to manipulate it. Besides illustrating SAS basic functions, you will see how each function can be used to get the information you need to improve business performance. Each chapter offers hands-on exercises drawn from real business situations. The book then provides an overview of statistics, as well as instruction on exploring data, preparing it for analysis, and testing hypotheses. You will learn how to use SAS to perform analytics and model using both basic and advanced techniques like multiple regression, logistic regression, and time series analysis, among other topics. The book concludes with a chapter on analyzing big data. Illustrations from banking and other industries make the principles and methods come to life. Readers will find just enough theory to understand the practical examples and case studies, which cover all industries. Written for a corporate IT and programming audience that wants to upgrade skills or enter the analytics field, this book includes: More than 200 examples and exercises, including code and datasets for practice. Relevant examples for all industries. Case studies that show how to use SAS analytics to identify opportunities, solve complicated problems, and chart a course. Practical Business Analytics Using SAS: A Hands-on Guide gives you the tools you need to gain insight into the data at your fingertips, predict business conditions for better planning, and make excellent decisions. Whether you are in retail, finance, healthcare, manufacturing, government, or any other industry, this book will help your organization increase revenue, drive down costs, improve marketing, and satisfy customers better than ever before.

Download or read book AI and IOT in Renewable Energy written by Rabindra Nath Shaw and published by Springer Nature. This book was released on 2021-05-12 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest research on applications of artificial intelligence and the Internet of Things in renewable energy systems. Advanced renewable energy systems must necessarily involve the latest technology like artificial intelligence and Internet of Things to develop low cost, smart and efficient solutions. Intelligence allows the system to optimize the power, thereby making it a power efficient system; whereas, Internet of Things makes the system independent of wire and flexibility in operation. As a result, intelligent and IOT paradigms are finding increasing applications in the study of renewable energy systems. This book presents advanced applications of artificial intelligence and the internet of things in renewable energy systems development. It covers such topics as solar energy systems, electric vehicles etc. In all these areas applications of artificial intelligence methods such as artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above, called hybrid systems, are included. The book is intended for a wide audience ranging from the undergraduate level up to the research academic and industrial communities engaged in the study and performance prediction of renewable energy systems.