Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles write by Teng Liu. This book was released on 2019-09-03. Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles available in PDF, EPUB and Kindle. 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.
Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles
Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles write by Teng Liu. This book was released on 2019-09-03. Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles available in PDF, EPUB and Kindle. 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.
Deep Reinforcement Learning-based Energy Management for Hybrid Electric Vehicles
Deep Reinforcement Learning-based Energy Management for Hybrid Electric Vehicles - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Deep Reinforcement Learning-based Energy Management for Hybrid Electric Vehicles write by Li Yeuching. This book was released on 2022-06-01. Deep Reinforcement Learning-based Energy Management for Hybrid Electric Vehicles available in PDF, EPUB and Kindle. The urgent need for vehicle electrification and improvement in fuel efficiency has gained increasing attention worldwide. Regarding this concern, the solution of hybrid vehicle systems has proven its value from academic research and industry applications, where energy management plays a key role in taking full advantage of hybrid electric vehicles (HEVs). There are many well-established energy management approaches, ranging from rules-based strategies to optimization-based methods, that can provide diverse options to achieve higher fuel economy performance. However, the research scope for energy management is still expanding with the development of intelligent transportation systems and the improvement in onboard sensing and computing resources. Owing to the boom in machine learning, especially deep learning and deep reinforcement learning (DRL), research on learning-based energy management strategies (EMSs) is gradually gaining more momentum. They have shown great promise in not only being capable of dealing with big data, but also in generalizing previously learned rules to new scenarios without complex manually tunning. Focusing on learning-based energy management with DRL as the core, this book begins with an introduction to the background of DRL in HEV energy management. The strengths and limitations of typical DRL-based EMSs are identified according to the types of state space and action space in energy management. Accordingly, value-based, policy gradient-based, and hybrid action space-oriented energy management methods via DRL are discussed, respectively. Finally, a general online integration scheme for DRL-based EMS is described to bridge the gap between strategy learning in the simulator and strategy deployment on the vehicle controller.
Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles
Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles write by Teng Liu. This book was released on 2022-06-01. Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles available in PDF, EPUB and Kindle. 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.
Intelligent Energy Management in Hybrid Electric Vehicles
Intelligent Energy Management in Hybrid Electric Vehicles - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Intelligent Energy Management in Hybrid Electric Vehicles write by Hamid Khayyam. This book was released on 2010. Intelligent Energy Management in Hybrid Electric Vehicles available in PDF, EPUB and Kindle. Intelligent Energy Management in Hybrid Electric Vehicles.
