A method of controlling battery preconditioning in a vehicle includes determining a first preconditioning characteristic of a first battery of a first vehicle relative to a charging station. The method further includes transmitting the first preconditioning characteristic. The method further includes receiving, from a second vehicle, a second preconditioning characteristic of a second battery relative to the charging station. The method further includes comparing the first preconditioning characteristic and the second preconditioning characteristic to determine a preconditioning ranking for the first vehicle and the second vehicle. The method further includes determining a queue of the first and second vehicles for the charging station using the preconditioning ranking of the first and second vehicles.

A vehicle includes a battery, an electric machine, and a controller. The battery has a state of charge. The electric machine is configured to draw electrical power from the battery to propel the vehicle in response to an acceleration request and to deliver electrical power to the battery to recharge the battery. The controller is programmed to adjust an estimation of battery state of charge based on a feed forward control that includes a coulomb counting algorithm, a first feedback control that includes a first battery model, and a second feedback control that includes a second battery model. The controller is further programmed to control the electrical power flow between the battery and the electric machine based on the estimation of the state of charge of the battery.

Techniques regarding parameterizing energy consumption of an electric vehicle are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a vehicle state estimation component that determines an operating condition experienced by a vehicle while traveling a route. Further, the system can comprise an energy consumption component that parametrizes an amount of energy expended by the vehicle while traveling the route based on a loss table that is populated with an energy consumption value derived from historic operation of the vehicle at the operating condition.

The present invention provides an artificial intelligence-based system for management of electric vehicles fleet. The system receives live data and historical data feeds from charging stations, fleet telematics, meteorological services, traffic management, mobile application, fleet dashboard, renewable source of energy, battery energy storage system, and the electric utility grid. The system utilizes machine learning algorithms to predict energy usage and optimize the charging schedule of electric vehicle. The system uses real time data to generate electric vehicle trip condition training feature for predicting the remaining driving range. The system predicts the vehicle's arrival time at the charging station based on telematics data of each vehicle collected from the fleet management system.

In one aspect, a method comprises receiving first data pertaining to a battery pack of a vehicle, wherein the first data is received from sensors associated with the vehicle, and the first data pertains to a battery pack current, a cell voltage, a cell current, a cell temperature, or some combination thereof; receiving second data pertaining to simulation of the battery pack; receiving third data from a manufacturer; receiving historical data on a fleet of vehicles that use the battery pack; predicting a remaining useful life of the battery pack of the vehicle by using a hybrid model comprising a physics-based model that receives the based on the first, second, third, and historical data, and generates properties pertaining to the battery pack; a machine learning model that uses the properties to predict the remaining useful life of each cell of the battery pack; and transmitting the remaining useful life.

A method of determining a preconditioning status of a vehicle component or system.

The method includes receiving a preconditioning status request for a vehicle component or system;

determining the preconditioning status by a preconditioning model estimating the preconditioning status without activating the corresponding vehicle component or system.

An electrified vehicle system includes an electric motor coupled to a drive wheel via a plurality of power transmission components and a control device. The control device is configured to act as: a feedforward control section configured based on a transfer function simulating vibration transmission characteristics of a power transmission system, receiving as an input a required torque of the electric motor from a driver, and outputting a base command torque of the electric motor; a timing estimation section estimating, based on information on the power transmission system, a timing at which a backlash between the plurality of power transmission components is eliminated; and a torque correction section applying, to the base command torque, a correction torque for reducing a vibration generated in the power transmission system due to elimination of the backlash, in response to an arrival of the timing estimated by the timing estimation section.

A method for detecting a fault state of at least one battery cell of a battery having multiple battery cells. A cell voltage of a respective battery cell of the multiple battery cells is registered at a measurement time and a comparison value is determined as a function of at least one of the cell voltages and is compared to a provided first reference value. The fault state is detected as a function of a result of the comparison. A scatter value is determined, which represents a scatter of at least part of the cell voltages registered at the specific measurement time, and the fault state is determined as a function of the scatter value.

A method for controlling the regenerative braking torque of a vehicle having a data processing unit for detecting a first information representing a deceleration request of the vehicle, detecting a second information representing a speed of the vehicle, and a first moving member of the vehicle and a second moving member of the vehicle. The method includes determining temperatures of different braking components on different axles, as well as the state of a battery module and a traction and regenerative braking module. The method also includes determining a regenerative braking power dynamic distribution ratio between the first and second axles. A regenerative braking torque is provided to one of the modules.

Circuitry for balancing cells in a battery pack, the circuitry comprising: cell balancing circuitry configured to transfer energy between cells of the battery pack in synchronisation with a clock signal; and control circuitry configured to control a parameter of the clock signal based on a monitored parameter or information associated with the battery pack.