Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Trajectory Optimization Based On Recursive B Spline Approximation For Automated Longitudinal Control Of A Battery Electric Vehicle
Download Trajectory Optimization Based On Recursive B Spline Approximation For Automated Longitudinal Control Of A Battery Electric Vehicle full books in PDF, epub, and Kindle. Read online Trajectory Optimization Based On Recursive B Spline Approximation For Automated Longitudinal Control Of A Battery Electric Vehicle ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Trajectory optimization based on recursive B-spline approximation for automated longitudinal control of a battery electric vehicle by : Jauch, Jens
Download or read book Trajectory optimization based on recursive B-spline approximation for automated longitudinal control of a battery electric vehicle written by Jauch, Jens and published by KIT Scientific Publishing. This book was released on 2024-03-01 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work describes a method for weighted least squares approximation of an unbounded number of data points using a B-spline function. The method can shift the bounded B-spline function definition range during run-time. The approximation method is used for optimizing velocity trajectories for an electric vehicle with respect to travel time, comfort and energy consumption. The trajectory optimization method is extended to a driver assistance system for automated vehicle longitudinal control.
Book Synopsis Trajectory Optimization Based on Recursive B-spline Approximation for Automated Longitudinal Control of a Battery Electric Vehicle by : Jens Jauch
Download or read book Trajectory Optimization Based on Recursive B-spline Approximation for Automated Longitudinal Control of a Battery Electric Vehicle written by Jens Jauch and published by . This book was released on 2023* with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Probabilistic Prediction of Energy Demand and Driving Range for Electric Vehicles with Federated Learning by : Thorgeirsson, Adam Thor
Download or read book Probabilistic Prediction of Energy Demand and Driving Range for Electric Vehicles with Federated Learning written by Thorgeirsson, Adam Thor and published by KIT Scientific Publishing. This book was released on 2024-09-03 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this work, an extension of the federated averaging algorithm, FedAvg-Gaussian, is applied to train probabilistic neural networks. The performance advantage of probabilistic prediction models is demonstrated and it is shown that federated learning can improve driving range prediction. Using probabilistic predictions, routing and charge planning based on destination attainability can be applied. Furthermore, it is shown that probabilistic predictions lead to reduced travel time.
Book Synopsis Predictive energy-efficient motion trajectory optimization of electric vehicles by : Guan, Tianyi
Download or read book Predictive energy-efficient motion trajectory optimization of electric vehicles written by Guan, Tianyi and published by KIT Scientific Publishing. This book was released on 2020-01-02 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Decision Making, Planning, and Control Strategies for Intelligent Vehicles by : Haotian Cao
Download or read book Decision Making, Planning, and Control Strategies for Intelligent Vehicles written by Haotian Cao and published by Springer Nature. This book was released on 2022-05-31 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: The intelligent vehicle will play a crucial and essential role in the development of the future intelligent transportation system, which is developing toward the connected driving environment, ultimate driving safety, and comforts, as well as green efficiency. While the decision making, planning, and control are extremely vital components of the intelligent vehicle, these modules act as a bridge, connecting the subsystem of the environmental perception and the bottom-level control execution of the vehicle as well. This short book covers various strategies of designing the decision making, trajectory planning, and tracking control, as well as share driving, of the human-automation to adapt to different levels of the automated driving system. More specifically, we introduce an end-to-end decision-making module based on the deep Q-learning, and improved path-planning methods based on artificial potentials and elastic bands which are designed for obstacle avoidance. Then, the optimal method based on the convex optimization and the natural cubic spline is presented. As for the speed planning, planning methods based on the multi-object optimization and high-order polynomials, and a method with convex optimization and natural cubic splines, are proposed for the non-vehicle-following scenario (e.g., free driving, lane change, obstacle avoidance), while the planning method based on vehicle-following kinematics and the model predictive control (MPC) is adopted for the car-following scenario. We introduce two robust tracking methods for the trajectory following. The first one, based on nonlinear vehicle longitudinal or path-preview dynamic systems, utilizes the adaptive sliding mode control (SMC) law which can compensate for uncertainties to follow the speed or path profiles. The second one is based on the five-degrees-of-freedom nonlinear vehicle dynamical system that utilizes the linearized time-varying MPC to track the speed and path profile simultaneously. Toward human-automation cooperative driving systems, we introduce two control strategies to address the control authority and conflict management problems between the human driver and the automated driving systems. Driving safety field and game theory are utilized to propose a game-based strategy, which is used to deal with path conflicts during obstacle avoidance. Driver's driving intention, situation assessment, and performance index are employed for the development of the fuzzy-based strategy. Multiple case studies and demos are included in each chapter to show the effectiveness of the proposed approach. We sincerely hope the contents of this short book provide certain theoretical guidance and technical supports for the development of intelligent vehicle technology.
Book Synopsis Deep Learning-based Eco-driving System for Battery Electric Vehicles by : Guoyuan Wu
Download or read book Deep Learning-based Eco-driving System for Battery Electric Vehicles written by Guoyuan Wu and published by . This book was released on 2019 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: Eco-driving strategies based on connected and automated vehicles (CAV) technology, such as Eco-Approach and Departure (EAD), have attracted significant worldwide interest due to their potential to save energy and reduce tail-pipe emissions. In this project, the research team developed and tested a deep learning–based trajectory-planning algorithm (DLTPA) for EAD. The DLTPA has two processes: offline (training) and online (implementation), and it is composed of two major modules: 1) a solution feasibility checker that identifies whether there is a feasible trajectory subject to all the system constraints, e.g., maximum acceleration or deceleration; and 2) a regressor to predict the speed of the next time-step. Preliminary simulation with microscopic traffic modeling software PTV VISSIM showed that the proposed DLTPA can achieve the optimal solution in terms of energy savings and a greater balance of energy savings vs. computational efforts when compared to the baseline scenarios where no EAD is implemented and the optimal solution (in terms of energy savings) is provided by a graph-based trajectory planning algorithm.
Book Synopsis Battery Management Algorithm for Electric Vehicles by : Rui Xiong
Download or read book Battery Management Algorithm for Electric Vehicles written by Rui Xiong and published by Springer Nature. This book was released on 2019-09-23 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book systematically introduces readers to the core algorithms of battery management system (BMS) for electric vehicles. These algorithms cover most of the technical bottlenecks encountered in BMS applications, including battery system modeling, state of charge (SOC) and state of health (SOH) estimation, state of power (SOP) estimation, remaining useful life (RUL) prediction, heating at low temperature, and optimization of charging. The book not only presents these algorithms, but also discusses their background, as well as related experimental and hardware developments. The concise figures and program codes provided make the calculation process easy to follow and apply, while the results obtained are presented in a comparative way, allowing readers to intuitively grasp the characteristics of different algorithms. Given its scope, the book is intended for researchers, senior undergraduate and graduate students, as well as engineers in the fields of electric vehicles and energy storage.
Book Synopsis Modeling and Dynamics Control for Distributed Drive Electric Vehicles by : Xudong Zhang
Download or read book Modeling and Dynamics Control for Distributed Drive Electric Vehicles written by Xudong Zhang and published by Springer Nature. This book was released on 2021-01-08 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the improvements on electric motors and motor control technology, alternative vehicle power system layouts have been considered. One of the latest is known as distributed drive electric vehicles (DDEVs), which consist of four motors that are integrated into each drive and can be independently controllable. Such an innovative design provides packaging advantages, including short transmission chain, fast and accurate torque response, and so on. Based on these advantages and features, this book takes stability and energy-saving as cut-in points, and conducts investigations from the aspects of Vehicle State Estimation, Direct Yaw Moment Control (DYC), Control Allocation (CA). Moreover, lots of advanced algorithms, such as general regression neural network, adaptive sliding mode control-based optimization, as well as genetic algorithms, are applied for a better control performance.
Book Synopsis Decision-making Strategies for Automated Driving in Urban Environments by : Antonio Artuñedo
Download or read book Decision-making Strategies for Automated Driving in Urban Environments written by Antonio Artuñedo and published by Springer Nature. This book was released on 2020-04-25 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes an effective decision-making and planning architecture for enhancing the navigation capabilities of automated vehicles in the presence of non-detailed, open-source maps. The system involves dynamically obtaining road corridors from map information and utilizing a camera-based lane detection system to update and enhance the navigable space in order to address the issues of intrinsic uncertainty and low-fidelity. An efficient and human-like local planner then determines, within a probabilistic framework, a safe motion trajectory, ensuring the continuity of the path curvature and limiting longitudinal and lateral accelerations. LiDAR-based perception is then used to identify the driving scenario, and subsequently re-plan the trajectory, leading in some cases to adjustment of the high-level route to reach the given destination. The method has been validated through extensive theoretical and experimental analyses, which are reported here in detail.
Book Synopsis Trajectory Planning for Automated Driving in Dynamic Environments by : Christian Lienke
Download or read book Trajectory Planning for Automated Driving in Dynamic Environments written by Christian Lienke and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Neural Dynamic Trajectory Design for Reentry Vehicles by : Ajay Verma
Download or read book Neural Dynamic Trajectory Design for Reentry Vehicles written by Ajay Verma and published by . This book was released on 2007 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: The next generation of reentry vehicles is envisioned to have onboard autonomous capability of real-time trajectory planning to provide capability of responsive launch and delivering payload anywhere with precise flight termination. This capability is also desired to overcome, if possible, in-flight vehicle damage or control effector failure resulting in degraded vehicle performance. An aerial vehicle is modeled as a nonlinear multi-input-multi-output (MIMO) system. An ideal optimal trajectory control design system generates a series of control commands to achieve a desired trajectory under various disturbances and vehicle model uncertainties including aerodynamic perturbations caused by geometric damage to the vehicle. Conventional approaches suffer from the nonlinearity of the MIMO system, and the high-dimensionality of the system state space. In this paper, we apply a Neural Dynamic Optimization (NDO) based approach to overcome these difficulties. The core of an NDO model is a multilayer perceptron (MLP) neural network, which generates the control parameters online. The advantage of the NDO system is that it is very fast and gives the trajectory almost instantaneously. The bulk of the time consuming computation is required only during off-line training. The inputs of the MLP are the time-variant states of the MIMO systems. The outputs of the MLP are the near optimal control parameters.
Book Synopsis Powertrain and Vehicle Longitudinal Motion Control for Personalized Eco-driving of P0+P4 Mild Hybrid Electric Vehicles by :
Download or read book Powertrain and Vehicle Longitudinal Motion Control for Personalized Eco-driving of P0+P4 Mild Hybrid Electric Vehicles written by and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the increasing trend of greenhouse gas emissions, the United States Environmental Protection Agency (EPA) has started to publish strict regulations regarding emissions for different types of vehicles. Battery electric vehicles (BEVs) have drawn much attention in recent years because they potentially eliminate all tailpipe emissions. However, due to charging speed and capacity limitations on battery, currently, EV users are facing the problem of range anxiety and the lack of charging stations. Hybrid electric vehicles (HEVs), which possess the advantages of both conventional vehicles and BEVs, appear to be a viable solution to cope with such strict emission regulations while mitigating range anxiety. Among all types of hybrid electric powertrain systems, a P0+P4 system possesses distinct advantages: two electric motors located on the front and rear axles allow brake energy to be recovered from both axles. Moreover, the dual motor configuration enables the driver to switch among front-drive, rear-drive and all-wheel-drive modes. Particularly, a 48V P0+P4 HEV requires less expensive wiring and electric shock protection and hence it is considered to be the most cost-effective HEV for reducing GHG emissions. This dissertation focusses on improving the energy efficiency, ride comfort, and safety of a 48V P0+P4 MHEV. To achieve these goals, this dissertation proposes a hierarchical control design among domains of power-split and vehicle longitudinal motion of 48V P0+P4 MHEV. In the domain of power-split, two real-time implementable controllers are proposed: (1) the optimization-based controller and (2) the learning-based controller. In the optimization-based control design, the approximated adaptive equivalent consumption minimization strategy (AA-ECMS) with a suboptimal braking distribution derived from dynamic programming (DP) analysis is proposed to capture the global optimal operation trends of the P0 motor operation, front/rear tire force distribution. In the learning-based control design, twin delayed deep deterministic policy gradient with prioritized exploration and experience replay (TD3+PEER), a novel prioritized exploration approach, is proposed to encourage the deep reinforcement learning (DRL) agent to explore states with complex dynamics. Both proposed power-split controllers achieve better fuel economy during the test trips compared to state-of-art rule-based and learning-based controllers. In vehicle longitudinal motion control design, two controllers have been developed using model predictive control (MPC): (1) the defensive ecological adaptive cruise control (DEco-ACC) and (2) the personalized one-pedal-driving (POPD). The DEco-ACC is a novel car-following algorithm that balances fuel economy, ride comfort, and avoidance of blind spots from neighboring vehicles. In DEco-ACC, a novel continuous and differentiable penalty function is proposed to describe the projection of several neighboring vehicles' blind spots to the ego vehicle's traffic lane. The proposed MPC-based controller considers this blind spot penalty function as a soft constraint within its prediction horizon; and is able to make its own decision to either yield, pass, or stay within the blind spots based on the MPC's cost function and the traffic scenario. The POPD is a novel personalized one-pedal driving method that can learn the individual driver's preference during everyday driving. In POPD, two types of MPC constraints that represent distinct driver's behavior are identified by analyzing 450 real-world drivers' data. And then, the POPD algorithm is validated in both the simulation environment and the human-in-the-loop (HIL) traffic simulator. These algorithms ensure car following safety and enhance the driver's comfort. The energy performance of DEco-ACC and POPD with proposed power-split algorithms are evaluated within corresponding chapters.
Book Synopsis Vehicle Propulsion Systems by : Lino Guzzella
Download or read book Vehicle Propulsion Systems written by Lino Guzzella and published by Springer Science & Business Media. This book was released on 2007-09-21 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors of this text have written a comprehensive introduction to the modeling and optimization problems encountered when designing new propulsion systems for passenger cars. It is intended for persons interested in the analysis and optimization of vehicle propulsion systems. Its focus is 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.
Book Synopsis Tire and Vehicle Dynamics by : Hans Pacejka
Download or read book Tire and Vehicle Dynamics written by Hans Pacejka and published by Elsevier. This book was released on 2012-04-12 with total page 649 pages. Available in PDF, EPUB and Kindle. Book excerpt: The definitive book on tire mechanics by the acknowledged world expert Covers everything you need to know about pneumatic tires and their impact on vehicle performance, including mathematic modeling and its practical application Written by the acknowledged world authority on the topic and the name behind the most widely used model, Pacejka’s ‘Magic Formula’ Updated with the latest information on new and evolving tire models to ensure you can select the right model for your needs, apply it appropriately and understand its limitations In this well-known resource, leading tire model expert Hans Pacejka explains the relationship between operational variables, vehicle variables and tire modeling, taking you on a journey through the effective modeling of complex tire and vehicle dynamics problems. Covering the latest developments to Pacejka's own industry-leading model as well as the widely-used models of other pioneers in the field, the book combines theory, guidance, discussion and insight in one comprehensive reference. While the details of individual tire models are available in technical papers published by SAE, FISITA and other automotive organizations, Tire and Vehicle Dynamics remains the only reliable collection of information on the topic and the standard go-to resource for any engineer or researcher working in the area. New edition of the definitive book on tire mechanics, by the acknowledged world authority on the topic Covers everything an automotive engineer needs to know about pneumatic tires and their impact on vehicle performance, including mathematic modelling and its practical application Most vehicle manufacturers use what is commonly known as Pacejka’s ‘Magic Formula’, the tire model developed and presented in this book
Book Synopsis Model-Based Predictive Control by : J.A. Rossiter
Download or read book Model-Based Predictive Control written by J.A. Rossiter and published by CRC Press. This book was released on 2017-07-12 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Predictive Control (MPC) has become a widely used methodology across all engineering disciplines, yet there are few books which study this approach. Until now, no book has addressed in detail all key issues in the field including apriori stability and robust stability results. Engineers and MPC researchers now have a volume that provides a complete overview of the theory and practice of MPC as it relates to process and control engineering. Model-Based Predictive Control, A Practical Approach, analyzes predictive control from its base mathematical foundation, but delivers the subject matter in a readable, intuitive style. The author writes in layman's terms, avoiding jargon and using a style that relies upon personal insight into practical applications. This detailed introduction to predictive control introduces basic MPC concepts and demonstrates how they are applied in the design and control of systems, experiments, and industrial processes. The text outlines how to model, provide robustness, handle constraints, ensure feasibility, and guarantee stability. It also details options in regard to algorithms, models, and complexity vs. performance issues.
Book Synopsis Practical Methods for Optimal Control and Estimation Using Nonlinear Programming by : John T. Betts
Download or read book Practical Methods for Optimal Control and Estimation Using Nonlinear Programming written by John T. Betts and published by SIAM. This book was released on 2010-01-01 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: A focused presentation of how sparse optimization methods can be used to solve optimal control and estimation problems.
Book Synopsis Cam Design Handbook by : Harold A. Rothbart
Download or read book Cam Design Handbook written by Harold A. Rothbart and published by McGraw-Hill Professional Publishing. This book was released on 2004 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: Packed with hundreds of detailed illustrations! THE DEFINITIVE GUIDE TO CAM TECHNOLOGY! The transformation of a simple motion, such as rotation, into linear or other motion is accomplished by means of a cam -- two moving elements mounted on a fixed frame. Cam devices are versatile -- almost any specified motion can be obtained. If you work with industrial applications where precision is essential, the "Cam Design Handbook" is a key resource you'll need handy at all times. You'll find thorough, detailed coverage of cams in industrial machinery, automotive optimization, and gadgets and inventions. Written with tremendous practical insight by engineering experts, the "Cam Design Handbook" gathers the information you need to understand cam manufacture and design. Comprehensive in scope and authoritative in nature, the book delivers a firm grasp of: * The advantages of cams compared to other motion devices * Computer-aided design and manufacturing techniques * Numerical controls for manufacturing * Cam size and profile determination * Dynamics of high-speed systems Get comprehensive coverage of: * Basic curves * Profile geometry * Stresses and accuracy * Camwear life predictions * Cam system dynamics * And more!
