@article{1433413,
      recid = {1433413},
      author = {Zhang, Xudong},
      title = {Modeling and dynamics control for distributed drive  electric vehicles /},
      publisher = {Springer Vieweg,},
      address = {Wiesbaden :},
      pages = {1 online resource},
      year = {2021},
      abstract = {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.  About the author Xudong Zhang received the M.S. degree in  mechanical engineering from Beijing Institute of  Technology, China, and the Ph. D. degree in mechanical  engineering from Technical University of Berlin, Germany.  Since 2017, he has joined in Beijing Institute of  Technology as an Associate Research Fellow. His main  research interests include vehicle dynamics control,  autonomous vehicles, and power management of hybrid  electric vehicles.},
      url = {http://library.usi.edu/record/1433413},
      doi = {https://doi.org/10.1007/978-3-658-32213-7},
}