Intelligent vehicles, charging systems, and control logic for v2x demand-response income and capacity optimization

A non-transitory, computer-readable medium storing instructions executable by one or more processors of a vehicle controller to control a vehicle grid integration (VGI) operation of a host vehicle, the host vehicle having a rechargeable battery pack connectable to a charging station, the instructions, when executed by the one or more processors, causing the vehicle controller to perform operations comprising:

• receiving user-specific data input by an operator of the host vehicle;
• receiving crowd-sourced data output by third-party vehicles deemed operatively comparable to the host vehicle and located within a predefined region of the host vehicle;
• estimating, using a non-iterative and non-recursive closed-form battery life model based on the user-specific data and the crowd-sourced data, a predicted battery life of the rechargeable battery pack resulting from the host vehicle performing the VGI operation;
• determining, using the predicted battery life, a value proposition indicating a predicted value and a predicted battery capacity for the host vehicle performing the VGI operation;
• and
• transmitting a command signal to a resident subsystem of the host vehicle to execute an automated control operation for the VGI operation based on the value proposition.

A motor vehicle, comprising:

• a vehicle body with a passenger compartment;
• a plurality of road wheels attached to the vehicle body;
• a traction motor attached to the vehicle body and operable to drive one or more of the road wheels to thereby propel the motor vehicle;
• a traction battery pack attached to the vehicle body and electrically connected to the traction motor;
• and
• a vehicle controller programmed to:
• receive user-specific data input by an operator of the motor vehicle;
• receive crowd-sourced data output by multiple third-party vehicles deemed operatively comparable to the motor vehicle and located within a predefined region of the motor vehicle;
• estimate, using a non-iterative and non-recursive closed-form battery life model based on the user-specific data and the crowd-sourced data, a predicted battery life of the rechargeable battery pack resulting from the motor vehicle performing the VGI operation;
• determine, using the predicted battery life, a value proposition indicating a predicted value and a predicted battery capacity for the motor vehicle performing the VGI operation;
• and
• command a resident subsystem of the motor vehicle to execute an automated control operation for the VGI operation based on the value proposition.