A control device notifies a destination arrival time based on a required charging time in a state where the air conditioning device is operated when charging is included in a scheduled travel plan. Before the charging is executed, the control device makes a proposal for permission to restrict use of the air conditioning device during the charging. When the proposal is approved, the control device changes the destination arrival time based on a required charging time in a state where the use of the air conditioning device is restricted, and notifies the destination arrival time.

A control device notifies a destination arrival time based on a required charging time in a state where the air conditioning device is operated when charging is included in a scheduled travel plan. Before the charging is executed, the control device makes a proposal for permission to restrict use of the air conditioning device during the charging. When the proposal is approved, the control device changes the destination arrival time based on a required charging time in a state where the use of the air conditioning device is restricted, and notifies the destination arrival time.

A parallel charging-discharging management system of multiple batteries comprises a main control module, a charging dual-MOS control module, a discharging dual-MOS control module, a communication module, a voltage sampling module, a current sampling module, a temperature sampling module, an electric quantity display module and batteries; the main control module is connected with a charging dual-MOS control module, a discharging dual-MOS control module, a communication module, a voltage sampling module, a current sampling module, a temperature sampling module and an electric quantity display module; the charging dual-MOS control module is connected with a power supply, batteries and a main control module, the discharging dual-MOS control module is connected with the batteries; the main control module and the load, the current sampling module is connected with the batteries and the main control module; the temperature sampling module is connected with the main control module; it prevents battery discharging and isolates parallel batteries.

A vehicle electricity storage system includes a control device including: a calculation unit configured to calculate an internal resistance value of the battery based on the voltage value and the current value; a derivation unit configured to derive an estimated internal resistance value, which is an estimated value of the current internal resistance of the battery, based on the calculated internal resistance value calculated and the current voltage value; and a setting unit configured to set a charging electricity upper limit value, which is an upper limit value of charging electricity for charging the battery, based on the derived estimated internal resistance value, the current voltage value, and a current value at present. The derivation unit is configured to derive a greater value as the estimated internal resistance value, as a difference between an upper limit voltage value of the battery and the current voltage value becomes smaller.

A vehicle electricity storage system includes a control device including: a calculation unit configured to calculate an internal resistance value of the battery based on the voltage value and the current value; a derivation unit configured to derive an estimated internal resistance value, which is an estimated value of the current internal resistance of the battery, based on the calculated internal resistance value calculated and the current voltage value; and a setting unit configured to set a charging electricity upper limit value, which is an upper limit value of charging electricity for charging the battery, based on the derived estimated internal resistance value, the current voltage value, and a current value at present. The derivation unit is configured to derive a greater value as the estimated internal resistance value, as a difference between an upper limit voltage value of the battery and the current voltage value becomes smaller.

A battery system including a removable battery pack, including a plurality of battery cells and an interface for electrically and mechanically coupling to a load bearing device; a vehicle, including a power station for providing power to drive the vehicle, the power station including a port for accepting the removable battery pack; and a power tool including a port for accepting the removable battery pack.

An embodiment apparatus for an electric vehicle includes an indoor power outlet configured to receive power through one of a plurality of lines except for a single-phase alternating current (AC) charging line among three-phase AC input lines, a sensor configured to measure a required current of an electronic device connected to the indoor power outlet, and a controller configured to control a bidirectional on board charger of the electric vehicle based on the required current.

An embodiment apparatus for an electric vehicle includes an indoor power outlet configured to receive power through one of a plurality of lines except for a single-phase alternating current (AC) charging line among three-phase AC input lines, a sensor configured to measure a required current of an electronic device connected to the indoor power outlet, and a controller configured to control a bidirectional on board charger of the electric vehicle based on the required current.

A system and method for providing real-time distributed micro-grid optimization using price signals to the electrical grid system by allowing bi-directional electricity usage from a distributed network of energy storage stations to form a large, distributed resource for the grid. A machine learning optimization module ingests various forms of data-from grid telemetry to traffic data to trip-to-trip data and more-in order to make informed spatiotemporal decisions about optimal pricing signals as well as strategically placing and balancing energy stores across various regions to support optimum energy usage, risk mitigation, grid fortification, and revenue generation. Energy stores are then sent updated price signals and updated parameters as to the amount of energy to hold or release.

A system and method for providing real-time distributed micro-grid optimization using price signals to the electrical grid system by allowing bi-directional electricity usage from a distributed network of energy storage stations to form a large, distributed resource for the grid. A machine learning optimization module ingests various forms of data-from grid telemetry to traffic data to trip-to-trip data and more-in order to make informed spatiotemporal decisions about optimal pricing signals as well as strategically placing and balancing energy stores across various regions to support optimum energy usage, risk mitigation, grid fortification, and revenue generation. Energy stores are then sent updated price signals and updated parameters as to the amount of energy to hold or release.