Data processing: vehicles – navigation – and relative location – Vehicle control – guidance – operation – or indication – Transmission control
Reexamination Certificate
2001-08-17
2003-09-23
Chin, Gary (Department: 3661)
Data processing: vehicles, navigation, and relative location
Vehicle control, guidance, operation, or indication
Transmission control
C701S054000, C701S070000, C477S094000
Reexamination Certificate
active
06625535
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates in general to control systems in automatic transmissions and, specifically, to a powertrain braking control system adaptive to grade, mass, and brake temperature.
2. Description of the Art
A typical driver, when driving down a hill or a mountain, makes frequent application of the brakes (brake applies). In vehicles with automatic transmissions, the powertrain control may enable engine braking to assist or substitute for driver brake applies. This powertrain braking is a method for the powertrain to supply braking torque to the driven wheels. Adaptive braking in this fashion can improve driver comfort, provide ideal coast performance or driveability, and improve conventional disc or drum brake life. Generally, the ideal amount of powertrain braking is dependent upon the terrain and the combined vehicle weight. Although the vehicle dynamic equation of mass, grade, tractive efforts, rolling resistance, aerodynamic load, and acceleration is well known, real time solution of the equation using these factors has not been performed without a mass or grade sensor. Example prior art systems lump both grade and mass load together and compares it with a predetermined value based on speed, or simply looks at the vehicle deceleration rate to determine if powertrain braking is needed. These efforts fail to comprehend or adapt to different types of terrain. They also fail to adapt to brake temperature conditions.
Additionally, a driver's driving style and intentions also play an important factor in powertrain braking. Prior art developed various fuzzy and neurologic based algorithms based on brake switch and acceleration and accelerator pedal position to incorporate the driver's intentions. However, such existing logic is easily confused by light versus heavy brake applies.
SUMMARY OF THE INVENTION
The present invention provides a method and apparatus to provide an optimum amount of powertrain braking that adapts to grade, mass, and brake temperature. The invention performs a real time estimation of vehicle mass and road grade without the use of either a grade or mass sensor. Using the vehicle mass, road grade and the prior vehicle braking capability, powertrain braking control is predicted to achieve a coast performance target—deceleration as a function of vehicle speed. Fuzzy logic is used to evaluate driver intentions, grade load conditions, terrain conditions, brake conditions, and other vehicle information to determine the actual optimal powertrain braking control. In addition, a real time brake thermal model is developed to provide increased powertrain braking under extreme brake conditions. Finally, available tractive efforts are continuously monitored to limit powertrain braking efforts to insure vehicle stability.
By delivering the same desirable vehicle coast performance under various terrain and load conditions, enhanced brake performance is achieved as a secondary benefit. Downhill rides will be more comfortable since the driver will not be preoccupied with controlling the vehicle speed with frequent brake applies. The invention is intended to significantly reduce the amount of energy the brake absorbs during downhill driving, resulting in an improvement in brake life. Since the algorithm of the present invention is math based, development efforts in calibration and validation are minimal. Additionally, the algorithms rely on sensors commonly used on powertrains, allowing a common or portable implementation approach for multiple applications without additional equipment costs.
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Berger Todd R.
Han Ed E.
Chin Gary
General Motors Corporation
Simon Anthony Luke
LandOfFree
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