Development & Integration of a Charge Sustaining Control Strategy for a Series-Parallel Plug-In Hybrid Electric Vehicle

Paper #:
  • 2014-01-2905

  • 2014-10-13
  • 10.4271/2014-01-2905
Manning, P., White, E., Marquez, E., Figueroa, L. et al., "Development & Integration of a Charge Sustaining Control Strategy for a Series-Parallel Plug-In Hybrid Electric Vehicle," SAE Technical Paper 2014-01-2905, 2014, doi:10.4271/2014-01-2905.
The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2012-2014 EcoCAR 2: Plugging in to the Future Advanced Vehicle Technology Competition series organized by Argonne National Lab (ANL), and sponsored by General Motors Corporation (GM) and the U.S. Department of Energy (DOE). The goals of the competition are to reduce well-to-wheel (WTW) petroleum energy consumption (PEU), WTW greenhouse gas (GHG) and criteria emissions while maintaining vehicle performance, consumer acceptability and safety. Following the EcoCAR 2 Vehicle Development Process (VDP), HEVT is designing, building, and refining an advanced technology vehicle over the course of the three year competition using a 2013 Chevrolet Malibu donated by GM as a base vehicle. The team selected a series-parallel Plug-In Hybrid Electric Vehicle (PHEV) with P2 (between engine and transmission) and P4 (rear axle) motors, a lithium-ion battery pack, an internal combustion engine, and an automatic transmission as the final powertrain of choice.Development of a charge sustaining control strategy for this vehicle involves coordination of controls for each of the main powertrain components through a distributed control strategy. This distributed control strategy includes component controllers for each individual component and a single supervisory controller responsible for interpreting driver demand and determining component commands to meet the driver demand safely and efficiently. The charge sustaining strategy is based on a simplified estimate of best powertrain efficiency under current load conditions including constraints such as battery state of charge, time between mode transitions, and drivability. For example, the algorithm will account for a variety of system operating points and will penalize or reward certain operating points for other conditions. These conditions include but are not limited to rewards for discharging the battery when the state of charge (SOC) is above the target value or penalties for operating points with excessive emissions. Development of diagnostics and remedial actions is an important part of controlling the powertrain safely. In order to validate the control strategy prior to in vehicle operation, it is necessary to run simulations against a plant model of the vehicle systems. This plant model can be run in both controller Software- and controller Hardware-In-the-Loop (SIL and HIL) simulations.This paper details the development of the controls for diagnostics, major selection algorithms, and execution of commands and its integration into the series-parallel PHEV through the supervisory controller. It also covers the plant model development and testing of the control algorithms using controller SIL and HIL methods. It details reasons for any changes to the control system, and describe improvements or tradeoffs that had to be made to the control system architecture for the vehicle to run reliably and meet its target specifications. SIL test data is presented from development and compared to corresponding controller HIL data and some bench testing or in vehicle data. These test results illustrate how changes to the plant model and control code properly affect operation of the control system in the actual vehicle.
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