A vehicle is provided to output an optimal driving path. The vehicle includes a battery storing an electric energy and a storage storing a position of a vehicle return location and an electric vehicle fuel economy value for each road type. A communicator receives delivery information including position information of a destination, and external information including real-time traffic information, road information, real-time temperature information, or charging station information. A controller determines a driving path based on information, determines the electric energy required for driving on the driving path based on the road type and the electric vehicle fuel economy value for each road type, determines whether the vehicle is capable of driving on the driving path based on a battery SOC and the determined required electric energy, and determines a final path based on the presence of a ramp with a slope greater than a preset slope.

A submergence data detection device includes a vehicle data acquisition unit configured to acquire vehicle data including at least acceleration data and estimation data for acquiring a drive power value and a traveling resistance value, and a submergence data detection unit configured to detect submergence data based on the vehicle data by a detection method including comparison of a threshold value set according to a calculated value of an acceleration of the vehicle calculated from the drive power value and the traveling resistance value with an actual value of the acceleration, and adjust the detection method according to whether or not a traveling state indicated by the vehicle data corresponds to a first state, in which reliability of the calculated value of the acceleration is degraded, such that detection accuracy of the submergence data in the first state is improved.

A power management system includes a sensor interface that receives sensor data samples during operation of a vehicle. A storage device stores the sensor data samples for multiple points in time along a route segment traveled by the vehicle. One or more processors analyze the sensor data samples to detect a historical pattern of the vehicle. The one or more processors determine time efficient operational parameters for the vehicle in response to a destination and an estimated travel time to the destination. The estimated travel time may be based on predicted conditions of the vehicle indicated by the historical pattern. The time efficient operational parameters may be selected to decrease the estimated travel time. At least one of the sensor data samples may include telemetry data.

A controller is applied to a vehicle including an engine (11) and a motor generator (12 and 13) as power sources of the vehicle and a battery (20) that transfers power with the motor generator. The controller charges the battery with a regeneration power that is a power regenerated by the motor generator when the vehicle is decelerated. The controller includes a SOC prediction unit (39, 50 and 205) to predict a SOC indicating a remaining capacity of the battery in a scheduled travel route of the vehicle, based on a predicted result of a road grade and a vehicle speed in the scheduled travel route, a discharge control unit (39, 52, 206, 208 and 301 to 303) to execute a discharge increasing control to previously increase a discharge quantity of the battery to prevent the battery from becoming in a saturation state based on a predicted SOC that is the SOC predicted by the SOC prediction unit, when the discharge control unit determines that the battery becomes in the saturation state where the battery cannot be charged with the regeneration power based on the predicted SOC, a determination unit (39 and 105 to 109) to determine whether a behavior of the predicted SOC shifts from a behavior of an actual SOC or determine whether a SOC shift factor occurs, after a start of the discharge increasing control, where the SOC shift factor is a vehicle control or an environment change that predicts the behavior of the predicted SOC shifts from the behavior of the actual SOC, and a correction unit (39, 110, 201 to 209 and 301 to 303) to correct the discharge increasing control by executing a prediction of the SOC in the scheduled travel route again, when the determination unit determines that the behavior of the predicted SOC shifts from the behavior of the actual SOC or determines that the SOC shift factor occurs.

A system for multiple brakes intelligently controlled by a single brake input on a personal mobility vehicle. By determining a front and rear brake differential based on the position and weight of the rider as well as the environmental and vehicle conditions, the system may reduce the risk of the vehicle skidding or tipping due to over-braking. In some embodiments, a rider may use a single brake lever to indicate a desire to brake and the system may make determinations about how to apply a combination of mechanical and electrical brakes to front and back wheels. By applying different braking systems based on a combination of controls and sensors, the system may improve user experience and user safety, especially for inexperienced riders.

A system and method for managing braking in a degraded adhesion condition for a vehicle system including at least one vehicle comprising setting a target deceleration value, applying a non-degraded braking force via a braking system of the vehicle system, detecting a presence of a degraded adhesion condition between the vehicle system and a route along which the vehicle system moves. Responsive to the degraded adhesion condition not being detected, maintaining the application of the non-degraded braking force, or responsive to the degraded adhesion condition being detected, applying a degraded braking force, activating recovery means to control deceleration of the vehicle system, determining a compensation deceleration value, and applying at least one of the braking system or recovery means to control the deceleration of the vehicle system.

The motor vehicle comprises a first motor configured to drive front wheels; a second motor configured to drive rear wheels; and a control device configured to control the first motor and the second motor, such that the motor vehicle is driven with a required torque for driving. The control device controls the first motor and the second motor to set a larger value to a rear wheel distribution ratio that is a ratio of a torque of the rear wheels to the required torque, when the motor vehicle runs on a low road having a road surface friction coefficient equal to or less than a predetermined value and is currently turned, compared with a value when the motor vehicle does not run on the low road or when the motor vehicle is not currently turned.

A hybrid power train structure for off-road vehicles (ATVs, UTVs and SSVs) uses an internal combustion engine (ICE) rotating a crankshaft through a continuously variable transmission (CVT) as a primary source of locomotion torque, but also includes a driving/generator motor which, in certain established conditions, can either provide an additional or alternative source of locomotion torque or can harvest electricity from the torque created by the internal combustion engine. The driving/generator motor is an axial flux motor of small size for its relative torque output, which can either be directly coupled to the CVT output shaft or, when additionally used as a starter motor for the ICE in an automatic ICE starting and stopping routine.

The configuration includes: a motor for driving a driving wheel (rear wheel) provided to a body; a slip ratio calculating section for calculating a slip ratio while the lawn mower is traveling; a friction coefficient calculating section for calculating a friction coefficient of a ground on which the lawn mower is traveling; a determination section for determining whether the ground on which the lawn mower is traveling is a lawn based on a relationship between the slip ratio and the friction coefficient and a drive controlling section for controlling the motor based on a determination result from the determination section. This configuration allows suitable driving operability for both of a case where the ground on which a lawn mowers traveling is a lawn and a case where the ground is other than a lawn.

Embodiments described herein relate to the field of transport, particularly motor vehicles. A motor with predictive adjustment is described, as well as a motor controller of a vehicle, which is capable of automatically adjusting a physical parameter of a motor, such as the width of the air gap of an electric motor. A motor of a vehicle can include at least one physical parameter capable of being adjusted according to characteristic data predicted from the current path of the vehicle based on data provided by at least one vehicle motor sensor. Thus, the motor can be automatically adjusted according to characteristic data predicted from the current path based on the data of a motor sensor for optimizing the use of the motor, with respect to a parameter such as power consumption, transmission efficiency, or rotor warming, regardless of the route.