Method and system for a hybrid power control in a vehicle
Methods and systems for improving fuel economy and reducing emissions of a vehicle with an electric motor, an engine, an energy storage device, and a controller are disclosed. The method includes obtaining current state information including a current hybrid control surface, and determining a target hybrid control surface for the vehicle based on the current state information.
1. A method for improving fuel economy and reducing emissions of a vehicle with an electric motor, an engine, and a controller, the method comprising:
obtaining, by the controller, (1) lookahead information including a predicted temperature of an aftertreatment system operatively coupled to the engine and (2) current state information including a current hybrid control surface; and
determining, by the controller based on the lookahead information and the current state information, a target power demand for the vehicle and a target hybrid control surface for the vehicle,
wherein the target hybrid control surface includes a first portion of the power demand associated with the engine and a second portion of the power demand associated with the motor, and
wherein the first portion is greater than 100% of the target power demand, and the second portion is a negative value such that a fraction of the first portion which exceeds 100% of the target power demand is converted into electrical energy via the motor.
2. The method of claim 1 , further comprising:
transitioning, by the controller, from the current hybrid control surface to the target hybrid control surface when the target hybrid control surface is different from the current hybrid control surface.
3. The method of claim 1 , wherein each of the current and target hybrid control surfaces is associated with at least one of: an altitude, an environmental condition, and an internal system state of the vehicle.
4. The method of claim 1 , wherein the obtaining the lookahead information includes obtaining predicted driving conditions or predicted traffic information of a route taken by the vehicle.
5. The method of claim 1 , wherein the obtaining the lookahead information includes obtaining predicted changes in a mass of the vehicle.
6. The method of claim 1 , wherein the obtaining the lookahead information includes obtaining predicted operating temperatures of electronics within the vehicle.
7. The method of claim 1 , wherein the obtaining the lookahead information includes obtaining predicted dosing amount and, timing of a catalyst used in the aftertreatment system operatively coupled to the engine.
8. The method of claim 1 , wherein the lookahead information is provided via telematics.
9. A method for improving fuel economy and reducing emissions of a vehicle with an electric motor, an engine, and a controller, the method comprising:
obtaining, by the controller, current state information;
learning, by the controller, a history of actions indicative of previous routes taken by an operator of the vehicle; and
determining, by the controller, a target power demand for the vehicle and a target state for the vehicle based on, the history of actions and the current state information,
wherein the target state includes a first portion of the power demand associated with the engine and a second portion of the power demand associated with the motor, and
wherein the first portion is greater than 100% of the target power demand, and the second portion is a negative value such that a fraction of the first portion which exceeds 100% of the target power demand is converted into electrical energy via the motor.
10. The method of claim 9 , further comprising:
obtaining, by the controller, lookahead information, such that the target state is determined based on the history of actions indicative of operator behavior, the lookahead information, and the current state information.
11. The method of claim 9 , wherein the history of actions indicative of operator behavior is implemented in a historically built database of road pattern expectations.
12. The method of claim 11 , wherein the database is implemented in a processing unit accessible by the controller wirelessly from a remote location, wherein the processing unit is a remote server in a cloud computing environment.
13. The method of claim 10 , wherein the obtaining the lookahead information includes obtaining predicted driving conditions or predicted traffic information of a route taken by the vehicle.
14. The method of claim 10 , wherein the obtaining the lookahead information includes obtaining predicted changes in a mass of the vehicle.
15. The method of claim 10 , wherein the obtaining the lookahead information includes obtaining predicted operating temperatures of electronics within the vehicle.
16. The method of claim 10 , wherein the obtaining the lookahead information includes obtaining predicted dosing amount and timing of a catalyst used in an aftertreatment system operatively coupled to the engine.
17. A vehicle comprising:
an electric motor, an engine, and a controller operatively coupled with the electric motor and the engine, the controller configured to:
obtain (1) lookahead information including a predicted temperature of an aftertreatment system operatively coupled to the engine and (2) current state information including a current hybrid control surface;
determine, based on the lookahead information and the current state information, a target power demand for the vehicle and a target hybrid control surface for the vehicle,
wherein the target hybrid control surface includes a first portion of the power demand associated with the engine and a second portion of the power demand associated with the motor, and
wherein the first portion is greater than 100% of the target power demand, and the second portion is a negative value; and
control, based on the first portion and the second portion that are determined, the motor to convert a fraction of the first portion which exceeds 100% of the target power demand into electrical energy.
18. The vehicle of claim 17 , wherein the controller is further configured to transition from the current hybrid control surface to the target hybrid control surface when the target hybrid control surface is different from the current hybrid control surface.
19. The vehicle of claim 17 , wherein the lookahead information further includes predicted changes in a mass of the vehicle.
20. The vehicle of claim 17 , wherein the controller is further configured to learn a history of actions indicative of operator behavior taken by an operator of the vehicle during previous trips, wherein the target state for the vehicle is further determined based on the history of actions indicative of operator behavior and the current state information.