skip to main content

Title: Online Identification of Power Required for Self-Sustainability of the Battery in Hybrid Electric Vehicles

Hybrid electric vehicles have shown great potential for enhancing fuel economy and reducing emissions. Deriving a power management control policy to distribute the power demanded by the driver optimally to the available subsystems (e.g., the internal combustion engine, motor, generator, and battery) has been a challenging control problem. One of the main aspects of the power management control algorithms is concerned with the self-sustainability of the electrical path, which must be guaranteed for the entire driving cycle. This paper considers the problem of identifying online the power required by the battery to maintain the state of charge within a range of the target value. An algorithm is presented that realizes how much power the engine needs to provide to the battery so that self-sustainability of the electrical path is maintained.
  1. ORNL
Publication Date:
OSTI Identifier:
DOE Contract Number:
Resource Type:
Resource Relation:
Conference: ASME 2014 Internal Combustion Engine Division Fall Technical Conference, Columbus, IN, IN, USA, 20141019, 20141022
Research Org:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). National Transportation Research Center (NTRC)
Sponsoring Org:
USDOE Laboratory Directed Research and Development (LDRD) Program
Country of Publication:
United States
model identification; hybrid electric vehicles; power management control; stochastic control; fuel economy