Abstract: A control system for a hybrid vehicle with an internal combustion engine and an electric motor includes a zone in which the hybrid vehicle can move is divided in advance into a restriction zone in which the operation of the internal combustion engine should be restricted, and an allowable zone in which the operation of the internal combustion engine is permitted. A new route is computed if an SOC of a battery of the hybrid vehicle is lower than a predetermined threshold value while the hybrid vehicle is located within the restriction zone when the hybrid vehicle moves along a computed route, or if the SOC is predicted to be lower than the threshold value while the hybrid vehicle is located within the restriction zone when the hybrid vehicle is assumed to move along the computed route.

Abstract: The machine learning device includes a predicting part configured to use a machine learning model to predict predetermined information, an updating part configured to update the machine learning model, and a part information acquiring part configured to detect replacement of a vehicle part and acquire identification information of the vehicle part after replacement. The updating part is configured to receive a new machine learning model trained using training data sets corresponding to the vehicle part after replacement from a server and apply the new machine learning model to the vehicle, if a vehicle part relating to input data of the machine learning model is replaced with a vehicle part of a different configuration.

Abstract: A vehicle controller includes a processor configured to input an operating-condition parameter indicating an operating condition of a device into a learning model to calculate a control parameter indicating a control condition for causing the device to perform a desired operation corresponding to the operating-condition parameter; correct the control parameter so as to achieve the control condition, based on a feedback value depending on an operation evaluating value; control the device in accordance with the control parameter when a predetermined accuracy condition concerning accuracy of control of the device performed in accordance with the control parameter is satisfied, and controls the device in accordance with the corrected control parameter when the predetermined accuracy condition is not satisfied.

Abstract: A control device for a hybrid vehicle includes a processor being configured to: set a target state of charge of the battery; control the internal combustion engine and rotating electric machine and charging and discharging of the battery to make the hybrid vehicle run, so that a state of charge of the battery becomes the target state of charge; and, in a case where a point inside a restricted region where operation of the internal combustion engine is restricted is set as a destination or a waypoint, set the target state of charge to a lower value when an estimated time of arrival at the destination or the waypoint is a point of time outside a restricted time period when operation of the internal combustion engine is restricted in the restricted region than when the estimated time of arrival is a point of time inside the restricted time period.

Abstract: A charge control system includes: a charging apparatus; and a charge control device including a processor calculating a charge amount of the charging apparatus and perform charging control. Further, the charge amount is calculated in a manner that a first charge amount is greater than a second charge amount, the first charge amount being the charger amount which is charged in a first time period which is from a predetermined reference time point until the engine driving prohibited zone is set, the second charge amount being the charger amount which is charged in a second time period which is from the predetermined reference time point until the engine driving prohibited zone is set, and the first time period being shorter than the second time period.

Abstract: A machine learning method performs training of values of model parameters forming a machine learning model, and is performed in a machine learning system including a vehicle having the machine learning model and a server able to communicate with the vehicle. The machine learning method includes: detecting, by the server, a current processing load of the server; determining, by the server, processing amounts of training respectively performed by the server and the vehicle, based on the processing load; performing, by the server, training of the values of the model parameters in accordance with the determined processing amount in the server; and performing, by the vehicle, training of the values of the model parameters in accordance with the determined processing amount in the vehicle. The server decreases a processing amount at the server when the processing load is relatively high compared to when it is relatively low.

Abstract: A contactless power feeding system includes: a power feeding device including a plurality of power feeding coils along a road, and configured to transmit electric power to a power receiving coil of an electric vehicle in a contactless manner; a receiver configured to receive traffic congestion information of the road; and an electronic control unit configured to: control transmission power transmitted from each of the plurality of power feeding coils to the power receiving coil, and control the power feeding device such that the transmission power of one or more power feeding coils located in a congestion occurrence section is higher than the transmission power of one or more power feeding coils located in a non-congestion occurrence section, wherein each of the congestion occurrence section and the non-congestion occurrence section are along a portion of the road including the plurality of power feeding coils.

Abstract: The control device of a vehicle includes a position estimating part configured to estimate a position of the vehicle, and a power output part configured to control the internal combustion engine and the electric motor to output power for running use. The power output part is configured to determine a startup position of the internal combustion engine of the vehicle when the vehicle exits from a low emission zone requesting the internal combustion engine be stopped so that startup positions of internal combustion engines of a plurality of vehicles are dispersed at surroundings of the low emission zone.

Abstract: A charging control system includes: a charging apparatus including a first processor, the charging apparatus being configured to store electric power to be supplied in a predetermined area; a charging stand provided in the predetermined area and including a second processor, the charging stand being configured to supply the electric power supplied from the charging apparatus to one or more electric vehicles in the predetermined area; and a charging control apparatus including a third processor, the third processor being configured to calculate number of the one or more electric vehicles in the predetermined area, calculate a charging amount of the charging apparatus based on the calculated number of the one or more electric vehicles, and perform charging control of the charging apparatus based on the calculated charging amount.

Abstract: A charging control system includes: a charging apparatus including a first processor, the charging apparatus being configured to store electric power to be supplied to a preset area; an equipment group provided in the preset area and including a second processor, the equipment group being configured to be supplied with the electric power from the charging apparatus; and a charging control apparatus including a third processor, the third processor being configured to: predict an amount of atmospheric suspended particulate matter floating in the preset area; calculate, based on the predicted amount of the atmospheric suspended particulate matter, a removal electric power amount to be used to remove the atmospheric suspended particulate matter entering the equipment group; calculate a total electric power amount by adding the removal electric power amount to an electric power amount to be regularly supplied to the preset area; and perform charging control of storing electric power equal to or more than the total

Abstract: In a hybrid vehicle, when a host vehicle is predicted to enter the inside of an engine drive restricted zone where operation of an internal combustion engine (20) is restricted, it is judged if congestion occurs or congestion is predicted as occurring in at least one of a running route leading to the inside of the engine drive restricted zone and a running route at the inside of the engine drive restricted zone.

Abstract: A charge control system includes a charging apparatus including a first processor configured to cause the charging apparatus to store electric power to be supplied to a preset region, and a charge control apparatus including a second processor configured to calculate a charge amount of the charging apparatus and perform charging control for the charging apparatus based on the calculated charge amount, wherein when calculating the charge amount, the second processor calculates a charge amount to be larger in a case where the engine driving prohibited zone is set in the region than a charge amount in a case where the engine driving prohibited zone is not set in the region.

Abstract: A charge control system includes: a charging apparatus including a first processor to cause the charging apparatus to store electric power to be supplied to at least one preset facility; a facility server provided in the facility; and a charge control device including a second processor to acquire facility schedule information regarding a future schedule of the facility from the facility server, calculate an amount of electric power to be supplied to the facility based on a schedule of opening and closure of the facility included in the facility schedule information, and perform charging control for the charging apparatus based on the calculated amount of electric power.

Abstract: A charge control system includes: a charging apparatus including a first processor to cause the charging apparatus to store electric power to be supplied to a preset region; a facility group installed in the region, to be supplied with electric power from the charging apparatus, and including a second processor; and a charge control device including a third processor configured to predict a snowfall amount in the region, calculate a snow removal electric power amount for removing snow covering the facility group based on the predicted snowfall amount, and perform charge control for causing the charging apparatus to store electric power equal to or more than the calculated snow removal electric power amount.

Abstract: A charge control system includes: a charging device having a first processor configured to store electric power to be supplied to a preset area; and a charge control device having a second processor configured to acquire brightness information in the area, calculate a charge amount of the charging device on a basis of the acquired brightness information, and perform charge control of the charging device on a basis of the calculated charge amount. Further, when calculating the charge amount, the second processor calculates the charge amount in such a manner that the charge amount decreases as brightness in the area increases.

Abstract: A control device is configured to set a target state of charge of a battery and control an internal combustion engine and rotating electrical machine and the charging and discharging of the battery to make the hybrid vehicle run so that the battery state of charge becomes the target state of charge. The control device is further configured to set the target state of charge based on a remaining distance or required time from a current position up to a restricted zone in which operation of the internal combustion engine is restricted and a grace period from a current time to a time at which the restriction of operation of the internal combustion engine in the restricted zone is started.

Abstract: A machine learning device training a learning model unique to a vehicle is provided with: a processor configured to use training data sets including values of state parameters detected by detectors provided at the vehicle, to train the learning model; and if an abnormality occurs in values of a state parameter detected by a detector, acquire values of the state parameter, where an abnormality has occurred, detected by another vehicle under conditions matching detection conditions when the values of the state parameter included in the training data sets were detected by the detector. If an abnormality occurs in values of the state parameter detected by the detector, the training part uses training data sets including values acquired from another vehicle by the parameter value acquiring part, instead of the values of the state parameter where an abnormality has occurred detected by the detector, to train the leaning model.

Abstract: The control device of a hybrid vehicle for controlling a hybrid vehicle includes a position estimating part configured to estimate a position of the hybrid vehicle using the vehicle position detection device, a reliability calculating part configured to calculate a reliability of position information of the hybrid vehicle, and a power output part configured to control the internal combustion engine and the electric motor to output power for driving use. The power output part is configured to reduce the output of the internal combustion engine when the reliability is equal to or less than a reference value, compared to when the reliability is higher than the reference value.

Abstract: The home position estimation system includes a GNSS receiver, an object detection device for detecting an object in surroundings of the hybrid vehicle, an identifying part configured to identify the object detected by the object detection device, and a position estimating part configured to estimate a position of the hybrid vehicle based on an output of the GNSS receiver. If a predetermined condition is satisfied and the object identified by the identifying part is an object indicating a boundary of a low emission zone which requires that the internal combustion engine be stopped, the position estimating part is configured to judge whether the hybrid vehicle is located within the low emission zone, regardless of the output of the GNSS receiver, based on a result of identification by the identifying part.

Abstract: A vehicle drive route instruction system in a hybrid vehicle in which when it is judged that currently the vehicle is driving through the inside of the engine drive restriction zone where driving by the internal combustion engine is restricted, the internal combustion engine is made to stop operating, the electric motor is used to drive the vehicle, and the shortest route from the current position to the boundary of the inside of the engine drive restriction zone and the outside of the engine drive restriction zone is searched. When it is judged that the SOC amount will fall to the preset judgment standard when driving the vehicle through the searched shortest route from the current position to the boundary, an occupant of the vehicle is given information to guide the vehicle from the current position through the searched shortest route to the boundary.