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- Author: Xudong Zhang
- Publisher: Springer Vieweg
- ISBN-10: 3658322128
- ISBN-13: 9783658322120
- Format: 14.8 x 21 x 1.2 cm, softcover
- Language: English
- SAVE -10% with code: EXTRA
Modeling and Dynamics Control for Distributed Drive Electric Vehicles (e-book) (used book) | bookbook.eu
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Description
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.
EXTRA 10 % discount with code: EXTRA
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- Author: Xudong Zhang
- Publisher: Springer Vieweg
- ISBN-10: 3658322128
- ISBN-13: 9783658322120
- Format: 14.8 x 21 x 1.2 cm, softcover
- Language: English English
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.
Reviews