Energy Efficient Non-Road Hybrid Electric Vehicles
Advanced Modeling and Control
Nonfiction, Science & Nature, Science, Physics, Energy, Technology, Electronics, Circuits
| Author: | Marcus Quasthoff, Johannes Unger, Stefan Jakubek | ISBN: | 9783319297965 |
| Publisher: | Springer International Publishing | Publication: | February 10, 2016 |
| Imprint: | Springer | Language: | English |
| Author: | Marcus Quasthoff, Johannes Unger, Stefan Jakubek |
| ISBN: | 9783319297965 |
| Publisher: | Springer International Publishing |
| Publication: | February 10, 2016 |
| Imprint: | Springer |
| Language: | English |
This book analyzes the main problems in the real-time control of parallel hybrid electric powertrains in non-road applications that work in continuous high dynamic operation. It also provides practical insights into maximizing the energy efficiency and drivability of such powertrains.
It introduces an energy-management control structure, which considers all the physical powertrain constraints and uses novel methodologies to predict the future load requirements to optimize the controller output in terms of the entire work cycle of a non-road vehicle. The load prediction includes a methodology for short-term loads as well as cycle detection methodology for an entire load cycle. In this way, the energy efficiency can be maximized, and fuel consumption and exhaust emissions simultaneously reduced.
Readers gain deep insights into the topics that need to be considered in designing an energy and battery management system for non-road vehicles. It also becomes clear that only a combination of management systems can significantly increase the performance of a controller.
This book analyzes the main problems in the real-time control of parallel hybrid electric powertrains in non-road applications that work in continuous high dynamic operation. It also provides practical insights into maximizing the energy efficiency and drivability of such powertrains.
It introduces an energy-management control structure, which considers all the physical powertrain constraints and uses novel methodologies to predict the future load requirements to optimize the controller output in terms of the entire work cycle of a non-road vehicle. The load prediction includes a methodology for short-term loads as well as cycle detection methodology for an entire load cycle. In this way, the energy efficiency can be maximized, and fuel consumption and exhaust emissions simultaneously reduced.
Readers gain deep insights into the topics that need to be considered in designing an energy and battery management system for non-road vehicles. It also becomes clear that only a combination of management systems can significantly increase the performance of a controller.
