Development of an Adaptive, Fuzzy Logic-Based, Parallel
Hybrid Drivetrain Controller, 03-9132
Principal Investigators
Ashok Nedungadi
Mark Walls
Bapi Surampudi
Inclusive Dates: 04/01/99 - 12/31/00
Background - The motivation for undertaking this program was driven by the challenge of developing a novel parallel hybrid powertrain that is robust and reliable. The SwRI-designed hybrid powertrain, which is a radical departure from present hybrid powertrains, has the potential of increased fuel savings and emissions reduction. The challenge of this project is to design a controller based on adaptive learning and fuzzy logic to improve fuel economy and reduce emissions without compromising driveability or vehicle performance.
Approach - The primary objective is to improve the existing SwRI hybrid powertrain controller, so that it will perform more reliably and predictably. The application of adaptive controls, coupled with fuzzy logic, is key to resolving driveability concerns of the present SwRI powertrain. The proposed approach comprises first of designing and implementing an adaptive controller for the engine and motor of the existing SwRI parallel hybrid powertrain. Following hardware implementation of the adaptive controller, it will be tested over several driving profiles to ensure robustness and repeatability. Second, the research team proposes to develop a fuzzy logic-based supervisory controller that will select and transition the powertrain from one mode of operation (i.e., assist, charge, electric, or regeneration) to another in a smooth manner, without compromising emissions or driveability and without introducing instabilities. Finally, the team proposes to conduct fuel economy and emissions testing of the improved drivetrain using Institute expertise and capabilities.
Accomplishments - The parallel hybrid powertrain, which uses all off-the-shelf components, has been completely assembled and tested. The Institute has recently received Patent 6,110,066 on the developed parallel hybrid powertrain. Both the adaptive and supervisory fuzzy logic based controllers are operational and have been fully tested on various driving profiles. All four modes of the powertrain (electric, charge, assist, and regenerative braking) have been individually and collectively tested. The transitioning from one mode to the other has been analyzed for satisfactory driveability requirements. The developed hybrid powertrain was tested on a dynamometer. The measured fuel economy of this hybrid powertrain in a midsize vehicle (1,265 kilograms) was between 56 and 62 miles per gallon using the Federal Test Procedure (FTP) driving schedule and 56 mpg for the highway driving profile. The powertrain is available for licensing.
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This test stand was used to validate the powertrain and controller. |
