Method and system for determining a distance-to-empty charge in an electric vehicle

A system for predicting a driving range of an electric vehicle power source comprising:

• an on-board diagnostic (OBD) device configured to interface with an electric vehicle's engine control unit (ECU) via an OBD port to receive real-time vehicle data from a vehicle data management system, and stored electric vehicle data from an electric vehicle data storage system, where the vehicle data includes a timestamp, and for each timestamp, a current state of charge and a total energy consumption data set comprising at least one of:
• motor speed and torque data, input current and throttle data, or input current and voltage data, and where the vehicle data is collected over time for storage in the electric vehicle data storage system;
• a distance-to-empty predictor comprising executable instructions stored as computer programs in a memory system configured to control electric vehicle battery management operations;
• and
• a processor configured to execute the executable instructions of the computer programs of the distance-to-empty predictor to automatically control display of range information to a vehicle operator, where when executed, the distance-to-empty predictor:
• receives a sample set of vehicle data collected over a sample time period, T, prior to a current time from the electric vehicle storage system via the OBD device interfacing with the ECU, and receives a current temperature measurement from a geophysical position sensor integrated with the OBD device;
• automatically initializes in the memory system a predicted charge-to-empty to the state of charge at the current time, and a distance-to-empty to zero;
• automatically constructs in the memory system a first set of n epoch data structures, D(Tn), corresponding to n epochs, tn, in the sample time period, T, with an epoch duration, T/n, each epoch data structure comprising a total energy calculated by the processor using specific vehicle sensor data during each of the n epochs, which is calculated using the total energy consumption data set in the vehicle data, and where the epoch speed is calculated by the processor based on a distance data obtained from the vehicle's odometer or GPS coordinates traveled over each epoch;
• automatically generate in the memory system a predicted epoch data structure, D(Tn+1), including a predicted total energy consumed rate and a predicted epoch speed corresponding to a next epoch, tn+1, using the set of n epoch data structures, D(Tn), as inputs to a statistical model pre-trained with historical electric vehicle performance data to model a relationship between the total energy consumed rates and epoch speeds over a next epoch tn+1;
• automatically generate using the processor a predicted state of charge rate for the next epoch, tn+1, by inputting the temperature measurement and the predicted total energy consumption rate to a state of charge rate prediction model trained on electric vehicle battery discharge characteristics;
• automatically calculate using the processor a state of charge consumption by multiplying the predicted state of charge rate for the next epoch, tn+1, by the epoch duration;
• automatically calculate using the processor a predicted next epoch distance based on the predicted epoch speed and the epoch duration;
• automatically update in the memory system the distance-to-empty by adding the predicted next epoch distance to a current value of the distance-to-empty;
• automatically update in the memory system the predicted charge-to-empty by subtracting the state of charge consumption from a current value of the predicted charge-to-empty;
• automatically control a vehicle user interface display to report to a user interface the distance-to-empty when the predicted charge-to-empty is less than or equal to an EMPTY_VALUE;
• and
• when the predicted charge-to-empty is not less than or equal to EMPTY_VALUE:
• automatically construct in the memory system a next set of n data structures including the predicted data structure,
• D(Tn+1), and the most recent n−1 epoch data structures in the previous set of n epoch data structures and repeat generating a predicted epoch data structure for a next epoch, generating the predicted state of charge rate for a next epoch, estimating the state of charge consumption for the next epoch, calculating the predicted next epoch distance, and updating the distance-to-empty and predicted charge-to-empty until the predicted charge-to-empty is less than or equal to EMPTY_VALUE.