Abstract: Systems and methods for fleet management for a fleet of vehicles include collecting data associated with the fleet of vehicles including data associated with a plurality of vehicle operations affecting degradation of each vehicle in the fleet of vehicles, determining a composite score associated with the fleet of vehicles based on the collected data, the composite score associated with both an average score for the fleet and a standard deviation score associated with each vehicle in the fleet of vehicles, wherein a higher composite score relates to a slower degradation of the fleet of vehicles, and altering assignment of the plurality of vehicle operations assigned to each vehicle in the fleet of vehicles based on the composite score data to enable a higher composite score by equalizing an average degradation of the fleet of vehicles.

Abstract: A system and method for managing energy consumption across a fleet of telematic devices in a computing environment. The method includes receiving real time vehicle operation data from a fleet of telematic devices. The method further includes processing the received real time vehicle operation data using one or more artificial intelligence device integration models. Further, the method includes generating artificial intelligence-based energy management models for the fleet of telematic devices based on the real time vehicle operation data. Additionally, the method includes generating one or more energy management decisions for the fleet of telematic devices based on the generated one or more artificial intelligence-based energy management models. The method further includes managing the generated one or more energy management decisions for the fleet of telematic devices using a web application.

Abstract: Systems and methods are disclosed for providing optimized, multi-objective charge planning strategies for electrified vehicles of a vehicle fleet. The proposed systems and methods may utilize a multi-objective approach to charge planning. The multi-objective approach may account for factors such as time, wear, and cost to charge by assigning a cost value to each factor. The proposed systems and methods may further leverage charging at fleet owned/managed depots, public charging stations, and private, residential charging locations when solving the charging path optimization problem for each vehicle of the fleet.

Abstract: A system and method for evaluation of a route score for an electric vehicle are disclosed. The system includes a route path characteristic score computation subsystem configured to compute a route path characteristic score of one or more routes between two or more distant locations based on one or more topological parameters and one or more scheduled activity parameters, a traffic score computation subsystem configured to compute a traffic score in real-time, an environment score computation subsystem configured to compute an environment score in the real-time, an overall route score computation subsystem configured to compute an overall route score in the real-time, a vehicle-level route score computation subsystem configured to compute a vehicle-level route score for a particular electric vehicle, an overall fleet-level route score computation subsystem configured to compute an overall fleet-level route score after aggregating the vehicle-level route score.

Abstract: A system and method for managing energy consumption across a fleet of telematic devices in a computing environment. The method includes receiving real time vehicle operation data from a fleet of telematic devices. The method further includes processing the received real time vehicle operation data using one or more artificial intelligence device integration models. Further, the method includes generating artificial intelligence-based energy management models for the fleet of telematic devices based on the real time vehicle operation data. Additionally, the method includes generating one or more energy management decisions for the fleet of telematic devices based on the generated one or more artificial intelligence-based energy management models. The method further includes managing the generated one or more energy management decisions for the fleet of telematic devices using a web application.

Abstract: A system and method for evaluation of a route score for an electric vehicle are disclosed. The system includes a route path characteristic score computation subsystem configured to compute a route path characteristic score of one or more routes between two or more distant locations based on one or more topological parameters and one or more scheduled activity parameters, a traffic score computation subsystem configured to compute a traffic score in real-time, an environment score computation subsystem configured to compute an environment score in the real-time, an overall route score computation subsystem configured to compute an overall route score in the real-time, a vehicle-level route score computation subsystem configured to compute a vehicle-level route score for a particular electric vehicle, an overall fleet-level route score computation subsystem configured to compute an overall fleet-level route score after aggregating the vehicle-level route score.

Abstract: A system for monitoring and maintaining a fleet of electric vehicles is disclosed. A processing subsystem includes an electric vehicle data tracking module which tracks vehicle data associated with each electric vehicle in the fleet of electric vehicles. An electric vehicle objective computation module utilizes one or more predefined fleet-level objectives corresponding to each of the electric vehicles in the fleet of the electric vehicles, ranks the one or more predefined fleet-level objectives in a predefined order. A fleet score computation module employs a predefined score model to calculate a vehicle level score corresponding to each of the one or more fleet level objectives ranked in predefined order, calculates a fleet level score, computes a fleet-level aggregate score for the fleet of the electric vehicles. A generic fleet action implementation module utilizes an implemented fleet action model for predicting maintenance and performance of the fleet of the electric vehicles.

Abstract: Using observation agents, listening agents and notifying agents, a method and system provides for using distributed business data without the need to integrate the distributed data. In addition, the notification can occur in “real time” without batch processing.