Patent ID: 11920943
Assignee: nan
Field: Control (Instruments)
Classification: CPC G  B  Y | IPC B  G

Claim 0:
1. A method of charging an electric vehicle (EV) battery utilizing a specifically programmed artificial intelligence computer system for EV battery energy management and EV route guidance comprising:
a. storing in memory EV location information, EV designated origination location information, and EV designated destination location information;
b. storing in memory locations of a multiplicity of distributed battery charging stations or battery replenishment stations accessible to said EV in route from said EV designated origination location to said EV designated destination location;
c. storing in memory of said specifically programmed artificial intelligence computer system expert systems program code for said EV battery energy management and said EV route guidance between said EV designated origination location and said EV designated destination location;
d. said expert systems program code further comprising expert systems propositional logic statement relationships between EV battery energy management parameters and EV route guidance parameters;
e. wherein said expert systems propositional logic statement relationships are defined by one or more experts having particular expert knowledge of EV battery technology, roadway conditions, weather conditions, traffic conditions, accidents or other dangerous situations that affect decisions and selection of said EV best route of travel to reach appropriate battery charging or battery replenishment stations for said EV and said EV designated destination location;
f. artificial intelligence evaluation of potential routes of travel for said EV by said specifically programmed artificial intelligence computer system with said artificial intelligence evaluation based at least in part on EV battery energy management and EV route guidance parameter memberships in parameter subsets with expert system propositional logic parameter relationships defined by said one or more experts;
g. artificial intelligence generation of route advisory indices for potential routes of travel for said EV corresponding to battery replenishing stations in said EV vicinity wherein lower energy needed and/or lower route travel times will yield route advisory indices indicating route preference;
h. artificial intelligence selection of a particular EV route of travel by said specifically programmed artificial intelligence computer system based at least in part on comparisons of said route advisory indices from artificial intelligence evaluations of potential EV routes of travel; and,
i. wherein said artificial intelligence selection of a particular EV route of travel by said specifically programmed artificial intelligence computer system is further based on maintaining adequate battery charge level to reach said designated destination location of said EV.