ADVISOR

ADVISOR: a systems analysis tool for advanced vehicle modeling. This paper provides an overview of Advanced Vehicle Simulator (ADVISOR)—the US Department of Energy’s (DOE’s) ADVISOR written in the MATLAB/Simulink environment and developed by the National Renewable Energy Laboratory. ADVISOR provides the vehicle engineering community with an easy-to-use, flexible, yet robust and supported analysis package for advanced vehicle modeling. It is primarily used to quantify the fuel economy, the performance, and the emissions of vehicles that use alternative technologies including fuel cells, batteries, electric motors, and internal combustion engines in hybrid (i.e. multiple power sources) configurations. It excels at quantifying the relative change that can be expected due to the implementation of technology compared to a baseline scenario. ADVISOR’s capabilities and limitations are presented and the power source models that are included in ADVISOR are discussed. Finally, several applications of the tool are presented to highlight ADVISOR’s functionality. The content of this paper is based on a presentation made at the ‘Development of Advanced Battery Engineering Models’ workshop held in Crystal City, Virginia in August 2001


References in zbMATH (referenced in 10 articles )

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  1. Li, Guoqiang; Görges, Daniel: Energy management strategy for parallel hybrid electric vehicles based on approximate dynamic programming and velocity forecast (2019)
  2. Wu, Tiezhou; Ding, Yi; Xu, Yushan: Energy optimal control strategy of PHEV based on PMP algorithm (2017)
  3. Meyer, Richard T.; DeCarlo, Raymond A.; Pekarek, Steve: Hybrid model predictive power management of a battery-supercapacitor electric vehicle (2016)
  4. Wu, Xiaolan; Guo, Guifang; Bai, Zhifeng: Cloud model-based energy management strategy for parallel hybrid vehicles (2015)
  5. Meyer, Richard T.; Decarlo, Raymond A.; Meckl, Peter H.; Doktorcik, Chris; Pekarek, Steve: Hybrid model predictive power management of a fuel cell-battery vehicle (2013)
  6. Gadsden, S. A.; Al-Shabi, M.; Habibi, S. R.: Estimation strategies for the condition monitoring of a battery system in a hybrid electric vehicle (2011)
  7. Montazeri-Gh, M.; Asadi, M.: Intelligent approach for parallel HEV control strategy based on driving cycles (2011)
  8. Chan, Kuei-Yuan; Papalambros, Panos Y.; Skerlos, Steve J.: A method for reliability-based optimization with multiple non-normal stochastic parameters: a simplified airshed management study (2010)
  9. Liu, Cheng-Ze; Zhu, Xin-Jian: Simulation and analysis of energy optimization for pemfc hybrid system (2006)
  10. Montazeri-Gh, Morteza; Poursamad, Amir; Ghalichi, Babak: Application of genetic algorithm for optimization of control strategy in parallel hybrid electric vehicles (2006)