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Author: Tunan Shen Publisher: ISBN: 9783658369934 Category : Languages : en Pages : 0
Book Description
Tunan Shen aims to increase the availability of powertrain systems for autonomous electric vehicles by improving the diagnostic capability for critical faults. Following the fault analysis of powertrain systems in battery electric vehicles, the focus is on the electrical and mechanical faults of the electric machine. A multi-level diagnostic approach is proposed, which consists of multiple diagnostic models, such as a physical model, a data-based anomaly detection model, and a neural network model. To improve the overall diagnostic capability, a decision making function is designed to derive a comprehensive decision from the predictions of various operating points and different models. Contents Background and State of the Art Diagnosis of Electrical Faults in Electric Machines Diagnosis of Mechanical Faults in Electric Machines Target Groups Researchers and students of mechanical engineering, especially automotive powertrains in electric vehicles Research and development engineers in this field About the Author Tunan Shen did his PhD project at the Institute of Automotive Engineering (IFS), University of Stuttgart, Germany. Currently he is Software Developer for Cross Domain Computing Solutions at a German automotive supplier.
Author: Tunan Shen Publisher: Springer Nature ISBN: 3658369922 Category : Technology & Engineering Languages : en Pages : 144
Book Description
Tunan Shen aims to increase the availability of powertrain systems for autonomous electric vehicles by improving the diagnostic capability for critical faults. Following the fault analysis of powertrain systems in battery electric vehicles, the focus is on the electrical and mechanical faults of the electric machine. A multi-level diagnostic approach is proposed, which consists of multiple diagnostic models, such as a physical model, a data-based anomaly detection model, and a neural network model. To improve the overall diagnostic capability, a decision making function is designed to derive a comprehensive decision from the predictions of various operating points and different models.
Author: Donghai Hu Publisher: Springer Nature ISBN: 9811650519 Category : Technology & Engineering Languages : en Pages : 146
Book Description
This book introduces the application of nonlinear dynamics theory for driving system of electric vehicle and hybrid electric vehicle respectively. It establishes the dynamic models for driving system of electric vehicle and hybrid electric vehicle under various working conditions. And the nonlinear dynamics theory is applied to the qualitative analysis and quantitative calculation for the models. The theoretical analysis results are applied to guide the optimization of control strategies. In the end of each chapter, corresponding simulations or experiments are provided to verify the corresponding instances which are carefully selected. This book will give some guidance to readers when they deal with nonlinear dynamics problems of vehicles in the future and provide theoretical bases for the further study of the nonlinear dynamics for driving system of electric vehicle and hybrid electric vehicle. The book is written for engineer of electric vehicle and hybrid vehicle, teachers and students majoring in automobile and automation.
Author: Michael Paulweber Publisher: Springer ISBN: 3319321358 Category : Technology & Engineering Languages : en Pages : 435
Book Description
The book deals with the increasingly complex test systems for powertrain components and systems giving an overview of the diverse types of test beds for all components of an advanced powertrain focusing on specific topics such as instrumentation, control, simulation, hardware-in-the-loop, automation or test facility management. This book is intended for powertrain (component) development engineers, test bed planners, test bed operators and beginners.
Author: Ullekh Raghunatha Gambhira Publisher: ISBN: Category : Automated vehicles Languages : en Pages : 117
Book Description
In this thesis, a novel approach is presented for the powertrain optimization of electric autonomous transportation vehicles. Two applications of a Level 5 Autonomous Vehicle (AV) are investigated; pure Autonomous Driving (AD) and mixed Human and Autonomous Driving (HAD). The powertrain-system design process is demonstrated for both the applications. In addition, the tradeoffs in using a HAD optimized powertrain for autonomous driving, compared to an AD optimized powertrain is addressed. A system level model is developed in MATLAB and Simulink to predict low-frequency dynamics. Two architectures of the electric powertrain, single (Front Wheel Drive) and double motor (All Wheel Drive) are considered. The optimization problem is set up, which includes defining the objective function, design space, static constraints and inputs for AD and HAD. Comfort requirements for AVs constrain the permissible acceleration while driving. Autonomous drive cycles are represented by optimal trajectories subject to constraints. Optimal powertrains for both the applications are expressed as Pareto fronts. It is observed that there isn’t a particular trend between energy consumption and powertrain power, and even higher powered powertrains provide similar energy consumption values. The energy savings in driving autonomously is primarily attributed to the optimized trajectory, rather than optimized powertrain.
Author: Vipin Kumar Kukkala Publisher: Springer Nature ISBN: 3031280164 Category : Technology & Engineering Languages : en Pages : 782
Book Description
This book provides comprehensive coverage of various solutions that address issues related to real-time performance, security, and robustness in emerging automotive platforms. The authors discuss recent advances towards the goal of enabling reliable, secure, and robust, time-critical automotive cyber-physical systems, using advanced optimization and machine learning techniques. The focus is on presenting state-of-the-art solutions to various challenges including real-time data scheduling, secure communication within and outside the vehicle, tolerance to faults, optimizing the use of resource-constrained automotive ECUs, intrusion detection, and developing robust perception and control techniques for increasingly autonomous vehicles.
Author: J. Jones Publisher: Routledge ISBN: 1136899383 Category : Education Languages : en Pages : 238
Book Description
This book gives a sufficient grounding in mechanics for engineers to tackle a significant range of problems encountered in the design and specification of simple structures and machines. It also provides an excellent background for students wishing to progress to more advanced studies in three-dimensional mechanics.
Author: James D. Halderman Publisher: Pearson Higher Ed ISBN: 0133004260 Category : Transportation Languages : en Pages : 711
Book Description
This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Diagnosis and Troubleshooting of Automotive Electrical, Electronic, and Computer Systems, Sixth Edition, covers both automotive electrical and engine performance topics all in one book. NATEF-correlated, the text presents the principles and practices of diagnosis and troubleshooting of automotive electrical, electronic, and computer systems in a clear, concise format and at a level of detail that far exceeds most similar texts.
Author: Teng Liu Publisher: Springer Nature ISBN: 3031015037 Category : Technology & Engineering Languages : en Pages : 90
Book Description
Powertrain electrification, fuel decarburization, and energy diversification are techniques that are spreading all over the world, leading to cleaner and more efficient vehicles. Hybrid electric vehicles (HEVs) are considered a promising technology today to address growing air pollution and energy deprivation. To realize these gains and still maintain good performance, it is critical for HEVs to have sophisticated energy management systems. Supervised by such a system, HEVs could operate in different modes, such as full electric mode and power split mode. Hence, researching and constructing advanced energy management strategies (EMSs) is important for HEVs performance. There are a few books about rule- and optimization-based approaches for formulating energy management systems. Most of them concern traditional techniques and their efforts focus on searching for optimal control policies offline. There is still much room to introduce learning-enabled energy management systems founded in artificial intelligence and their real-time evaluation and application. In this book, a series hybrid electric vehicle was considered as the powertrain model, to describe and analyze a reinforcement learning (RL)-enabled intelligent energy management system. The proposed system can not only integrate predictive road information but also achieve online learning and updating. Detailed powertrain modeling, predictive algorithms, and online updating technology are involved, and evaluation and verification of the presented energy management system is conducted and executed.
Author: Tunan Shen
Author: Tunan Shen
Author: Donghai Hu
Author: Michael Paulweber
Author: Ullekh Raghunatha Gambhira
Author: Vipin Kumar Kukkala
Author: J. Jones
Author: 
Author: Wenbo Wang
Author: James D. Halderman
Author: Teng Liu