A vehicle-grid integration management system determines use of a power grid by an electric vehicle in a dual multi-part rate structure including a grid account portion associated with a relationship between the electric vehicle and the power grid, a group account portion associated with a relationship between the vehicle group and the electric vehicle and/or the power grid, a consumption portion associated with a volume of electricity drawn from the power grid by the electric vehicle over a time period, a supply portion associated with a volume of electricity delivered to the power grid by the electric vehicle over the time period, a demand portion associated with an upper threshold of electricity drawn from the power grid by the electric vehicle over the time period, and a capacity portion associated with an upper threshold of electricity delivered to the power grid by the electric vehicle over the time period.

A vehicle communication, power, and guidance system for use in guiding and communicating with a land vehicle along a roadway, the system comprising: one or more reference devices positioned along the roadway, each of the reference devices further comprising: a memory device for storing fixed values for one or more vehicle and traffic related parameters; and one or more transmission modules for transmitting said fixed values for one or more vehicle and traffic related parameters; a vehicle mounted device comprising: a receiving module for receiving transmitted signals from the transmission module of said reference devices; and a processing module for processing the received signals and a transmitter module to transmitting signals to the reference device to communicate with one or more controllers of the vehicle to guide and control movement of the vehicle along the roadway.

A method for operating an electrically operated or also electrically operable motor vehicle provided with a rechargeable electric energy storage device associated with the drive motor of the motor vehicle. A target charging state is determined for the energy storage device and an operating strategy is determined for a route that is calculated, entered or predicted for the next trip, by which recuperative deceleration is enabled with a specifiable minimum amount for deceleration processes occurring along the route. A total mass of the motor vehicle, including optionally a trailer connected to the motor vehicle, deviating from an input normal value and an air resistance of the motor vehicle deviating from a predetermined normal value are taken into account.

A charging amount calculation apparatus calculates an amount of power consumption by a battery for running along a running route and a during-running charging amount received by a power reception apparatus from at least one second power feeding facility. The charging amount calculation apparatus calculates a pre-running charging amount based on the amount of power consumption and the during-running charging amount.

A processing unit segments the route into a plurality of sections. It is, for each section, obtains a set of route section characteristic values, R.sub.SCV, that will impact the energy consumption of the vehicle whilst driving within the section, obtains a set of vehicle energy consumption values, V.sub.ECV, that will impact the energy consumption of the vehicle whilst driving within the section at least partly based on R.sub.SCV, estimates a first probability distribution, P.sub.1, of the energy consumption for the vehicle whilst driving within the section based on R.sub.SCV, V.sub.ECV, and a first set of traffic information values, T.sub.1, within the section, estimates a second probability distribution, P.sub.2, of the energy consumption for the vehicle whilst driving within the section based on R.sub.SCV, V.sub.ECV, and a second set of traffic information values, T.sub.2, within the section, estimates a traffic flow indicator, I.sub.TF, for the section based on R.sub.SCV, V.sub.ECV and a third set of traffic information values, T.sub.3, within the section, and determines a route section probability distribution, P.sub.RS, of the energy consumption for the vehicle whilst driving within the section based on the relation between I.sub.TF, P.sub.1, and P.sub.2.

Systems, methods, and storage media for generating a predicted discharge profile of a vehicle battery pack are disclosed. A method includes receiving, by a processing device, data pertaining to cells within a battery pack installed in each vehicle of a fleet of vehicles operating under a plurality of conditions, the data received from at least one of each vehicle in the fleet of vehicles, providing, by the processing device, the data to a machine learning server, directing, by the processing device, the machine learning server to generate a predictive model, the predictive model based on machine learning of the data, generating, by the processing device, the predicted discharge profile of the vehicle battery pack from the predictive model, and providing the discharge profile to an external device.

Submitted is an abnormality detection device including a processing unit, and a communication unit that can communicate with a ground electric power supply device that transmits electric power to a vehicle in a non-contact manner. The processing unit is configured to detect electricity theft or electricity leakage in the ground electric power supply device, based on a time dependent change pattern of an electric power supply amount of the ground electric power supply device or a parameter that is correlated to the electric power supply amount, the time dependent change pattern being a time dependent change mode.

The vehicle control device controls a vehicle configured to receive power by non-contact from a power transmission coil when passing over the power transmission coil. The vehicle control device includes a processor configured to set a target speed of the vehicle in a power supply area where the power transmission coil is installed. The processor is configured to lower the target speed when at least one predetermined condition is satisfied, compared to when the at least one predetermined condition is not satisfied. The at least one predetermined condition includes a first condition relating to a running environment around the vehicle.

A computing system can receive and compile power cell data, and in certain examples, the power cell data can be distributed to a distributed ledger. The computing system can further determine approximate battery end of life (ABEL) for each power cell based on a compiled historical record of power cell data. Based on the determined ABEL, the computing system can generate ABEL reports for users, determine optimal settings for a power cell or battery-powered device, and/or transmit notifications to users, to facilitate power cell usage optimization, and/or optimal repurposing or recycling timing.

An operating mode control device includes a travel driving force information acquisition unit configured to acquire a time-series travel driving force when traveling on a travel route; a vehicle speed information acquisition unit configured to acquire a time-series vehicle speed when traveling on the travel route; a motor operation estimation unit configured to estimate a time-series torque and rotation speed of the motor on the basis of a time-series travel driving force and vehicle speed; an efficiency calculation unit configured to acquire a time-series efficiency value of each operating mode on the basis of the time-series torque and rotation speed and calculate a total efficiency value; an operating mode determination unit configured to determine the operating mode having the highest total efficiency value as a default operating mode; and an operation control unit configured to control an operation by the default operating mode.