A network of collection, charging and distribution machines collects, charges and distributes portable electrical energy storage devices (e.g., batteries, supercapacitors or ultracapacitors). Vehicle diagnostic data of a vehicle using the portable electrical energy storage device is stored on a diagnostic data storage system of the portable electrical energy storage device during use of a respective portable electrical energy storage device by a respective vehicle. Once the user places the portable electrical energy storage device in the collection, charging and distribution machine, or comes within wireless communications range of a collection, charging and distribution machine, a connection is established between the collection, charging and distribution machine and the portable electrical energy storage device. The collection, charging and distribution machine then reads vehicle diagnostic data stored on the diagnostic data storage system of the portable electrical energy storage device and provides information regarding the diagnostic data.

A network of collection, charging and distribution machines collect, charge and distribute portable electrical energy storage devices (e.g., batteries, supercapacitors or ultracapacitors). Locations of collection, charging and distribution machines having available charged portable electrical energy storage devices are communicated to or acquired by a mobile device of a user, or displayed on a collection, charging and distribution machine. The locations are indicated on a graphical user interface on a map on a user's mobile device relative to the user's current location. The user may use their mobile device select particular locations on the map to reserve an available portable electrical energy storage device. The system nay also warn the user that the user is near an edge of the pre-determined area having portable electrical energy storage device collection, charging and distribution machines. Reservations may also be made automatically based on information regarding a potential route of a user.

An apparatus and a method for controlling a motor of an electric vehicle are disclosed. The apparatus receives a driving route for the electric vehicle and divides the driving route into sections. Each of the sections has one of two or more predefined road types. The apparatus calculates a motor control value for each of sections using pieces of past driving-related information of the electric vehicle for each one of the two or more predefined road types, and controls a motor of the electric vehicle based on the calculated motor control value. The electric vehicle may be an autonomous vehicle. In this case, the autonomous vehicle may be operated with an arbitrary artificial intelligence (AI) module, a drone, an unmanned aerial vehicle, a robot, an augmented reality (AR) module, a virtual reality (VR) module, a fifth generation (5G) mobile communication apparatus, or the like.

A system and method for navigating an autonomous driving vehicle (ADV) that utilizes an-onboard computer and/or one or more ADV control system nodes in an ADV network platform. The on-board computer receives battery monitoring and management data concerning a battery stack. The on-board computer, utilizing a battery management system, determines the current state of charge (SOC) and other information concerning the battery stack and determines if the estimated total amount of electrical power required to navigate an ADV along a generated route to reach the predetermined destination is available. In response to determining that the ADV cannot reach the predetermined destination, the on-board computer automatically initiates a dynamic routing algorithm, which utilizes artificial intelligence, to generate alternative routes in an effort to find a route that the ADV can navigate to reach the destination utilizing the current state of charge (SOC) of the battery stack.

Systems and methods for providing instructions associated with directions to a destination are disclosed. In some embodiments, an electric vehicle transmits a request for directions to a destination. The electric vehicle receives instructions, which are determined based on battery state-of-health of the electric vehicle, associated with the directions to the destination. The directions comprise an itinerary determined in accordance with the battery state-of-health.

A control method of an electric vehicle using one or a plurality of motors as a traveling drive source, includes: a motor torque command value calculating step that calculates a motor torque command value; an angular velocity detecting step that detects an angular velocity correlating with a rotation speed of a drive shaft which transmits a drive force of the motor to a drive wheel; a disturbance torque estimating step that estimates a disturbance torque acting on the motor based on the motor torque command value and the angular velocity; a limiting torque setting step that sets a limiting torque corresponding to the disturbance torque in a manner that a slipping rate of the drive wheel does not exceed a first predetermined value; and a motor torque limiting step that limits the motor torque command value using the limiting torque.

A system for controlling powertrain of an electric vehicle, comprising: a driver recognition module, configured for determining the identity information of the controlled vehicle's driver, and uploading the identity information to a backend computing unit; the backend computing unit, located at a remote end of the controlled vehicle, configured for generating a first control information based on the driver's identity information; an assist control module, configured for generating a second control information based on the information related to current driving of the controlled vehicle which is acquired from the backend computing unit; and a control information application module, integrated in the controlled vehicle, configured for applying the first and second control information to the powertrain of the controlled vehicle. Optimized control for powertrain is achieved and an excellent user experience is provided. The system can be implemented simply, and be updated and maintained conveniently.

This disclosure relates to an electrified vehicle configured to selectively deactivate a restricted power mode based on an acceleration request, such as an imminent or current acceleration request. A corresponding method is also disclosed. An example electrified vehicle includes a battery and a controller configured to apply a restricted power mode when a state of health of the battery is below a predefined lower threshold. Further, when in the restricted power mode, the controller is configured to limit an amount of power drawn from the battery. Additionally, the controller is configured to selectively deactivate the restricted power mode in response to a signal indicating a current or imminent request for acceleration of the electrified vehicle requiring power to be drawn from the battery above an upper limit of the restricted power mode.

A collection, charging and distribution machine collects, charges and distributes portable electrical energy storage devices (e.g., batteries, super- or ultracapacitors). To charge, the machine employs electrical current from an external source, such as the electrical grid or an electrical service of an installation location. The machine determines a first number of devices to be rapidly charged, employing charge from a second number of devices identified to sacrifice charge. Thus, some devices may be concurrently charged via current from the electrical service and current from other devices, to achieve rapid charging of some subset of devices. The devices that sacrifice charge may later be charged. Such may ensure availability of devices for end users.

An apparatus comprising an interface, a memory and a processor. The interface may be configured to receive sensor data samples during operation of a vehicle. The memory may be configured to store the sensor data samples over a number of points in time. The processor may be configured to analyze the sensor data samples stored in the memory to detect a pattern. The processor may be configured to manage an application of brakes of the vehicle in response to the pattern.