Fuzzy logic electric vehicle regenerative antiskid braking and traction control system
Abstract
An regenerative antiskid braking and traction control system using fuzzy logic for an electric or hybrid vehicle having a regenerative braking system operatively connected to an electric traction motor, and a separate hydraulic braking system includes sensors for monitoring present vehicle parameters and a processor, responsive to the sensors, for calculating vehicle parameters defining the vehicle behavior not directly measurable by the sensor and determining if regenerative antiskid braking control, requiring hydraulic braking control, and requiring traction control are required. The processor then employs fuzzy logic based on the determined vehicle state and provides command signals to a motor controller to control operation of the electric traction motor and to the brake controller to control fluid pressure applied at each vehicle wheel to provide the appropriate regenerative braking control, hydraulic braking control, and traction control.
- Inventors:
-
- Wixom, MI
- Issue Date:
- Research Org.:
- Ford Motor Company, Detroit, MI (United States)
- OSTI Identifier:
- 869570
- Patent Number(s):
- 5358317
- Assignee:
- Ford Motor Company (Dearborn, MI)
- Patent Classifications (CPCs):
-
B - PERFORMING OPERATIONS B60 - VEHICLES IN GENERAL B60L - PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES
B - PERFORMING OPERATIONS B60 - VEHICLES IN GENERAL B60T - VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF
- DOE Contract Number:
- AC07-90ID13019
- Resource Type:
- Patent
- Country of Publication:
- United States
- Language:
- English
- Subject:
- fuzzy; logic; electric; vehicle; regenerative; antiskid; braking; traction; control; hybrid; operatively; connected; motor; separate; hydraulic; sensors; monitoring; parameters; processor; responsive; calculating; defining; behavior; directly; measurable; sensor; determining; requiring; required; employs; based; determined; provides; command; signals; controller; operation; brake; fluid; pressure; applied; wheel; provide; appropriate; regenerative antiskid; motor controller; antiskid braking; traction motor; control fluid; command signal; electric traction; regenerative braking; hybrid vehicle; electric vehicle; operatively connected; fluid pressure; traction control; pressure applied; motor control; parameters defining; fuzzy logic; directly measurable; vehicle wheel; vehicle regenerative; /303/701/
Citation Formats
Cikanek, Susan R. Fuzzy logic electric vehicle regenerative antiskid braking and traction control system. United States: N. p., 1994.
Web.
Cikanek, Susan R. Fuzzy logic electric vehicle regenerative antiskid braking and traction control system. United States.
Cikanek, Susan R. Sat .
"Fuzzy logic electric vehicle regenerative antiskid braking and traction control system". United States. https://www.osti.gov/servlets/purl/869570.
@article{osti_869570,
title = {Fuzzy logic electric vehicle regenerative antiskid braking and traction control system},
author = {Cikanek, Susan R},
abstractNote = {An regenerative antiskid braking and traction control system using fuzzy logic for an electric or hybrid vehicle having a regenerative braking system operatively connected to an electric traction motor, and a separate hydraulic braking system includes sensors for monitoring present vehicle parameters and a processor, responsive to the sensors, for calculating vehicle parameters defining the vehicle behavior not directly measurable by the sensor and determining if regenerative antiskid braking control, requiring hydraulic braking control, and requiring traction control are required. The processor then employs fuzzy logic based on the determined vehicle state and provides command signals to a motor controller to control operation of the electric traction motor and to the brake controller to control fluid pressure applied at each vehicle wheel to provide the appropriate regenerative braking control, hydraulic braking control, and traction control.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {1994},
month = {1}
}