A method is used to control a fuel level gauge of a vehicle system and includes: monitoring, via an engine controller, a fuel economy of the vehicle system; comparing, via the engine controller, the fuel economy with a predetermined fuel economy threshold to determine whether the fuel economy is less than the predetermined fuel economy threshold; adjusting, via the engine controller, a sensitivity of a display filter in response to determining that the fuel economy is less than the predetermined fuel economy threshold for a predetermined amount of time in order to maximize an accuracy of the fuel level gauge, wherein the display filter smoothes an unfiltered fuel level signal received from a fuel level sensor of the vehicle system, thereby generating a filtered fuel level signal; and controlling, via an instrument panel controller, the fuel level gauge of the vehicle system.

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.

One way to improve fuel efficiency of a vehicle is to detect the vehicle operational shortcomings related to fuel consumption by determining whether fuel used during operation of the vehicle is normal fuel use or wasted fuel use. Considerations of idling, speeding and inappropriate gear shifts are some ways to measure the amount of fuel wasted due to operator shortcomings. Communicating this information to the operator in real-time so adjustments can be made will improve vehicle fuel efficiency. These techniques are applicable to tracking employment of other driving best practices as well.

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.

A vehicle includes: an instrument panel; and an ECU that controls the instrument panel so that the instrument panel displays an icon representing a status of a battery. The icon represents one of a first indication and a second indication by an increase or decrease of a scale in a display region of the icon, and the other one of the first indication and the second indication by an amount indicated by a size of a display area of the icon, the first indication representing SOC of the battery, the second indication representing a full charge capacity of the battery.

A method for outputting recommendations for energy efficient operation of a vehicle having at least two modes of operation, from which an operating mode is respectively selected by a drive controller, depending on the occurrence of specified triggers, for operating the vehicle. A change of operating mode caused by the trigger is determined. A frequency of the change of operating mode is incremented at every determination of the change of operating mode caused by the trigger. The frequency is analyzed by comparing the frequency of the change of operating mode a predetermined value. A message is generated on a case-by-case basis. The message is output via at least one output comprised by the vehicle.

A vehicle, system and method for improving driving efficiency for a first host vehicle with at least one propulsion unit and at least one energy storage unit are provided. The method comprises; determining a first set of parameters which affects driving efficiency before a driving session with the first host vehicle is initiated and providing input indicative thereof to a user interface or an autonomous or semi-autonomous driving system of the first host vehicle, monitoring a second set of parameters which affects driving efficiency during the driving session of the first host vehicle, comparing parameters of the first and second set of parameters with corresponding parameters received from at least one second host vehicle, and in response to identified differences between parameters of the first and second host vehicle, and providing input indicative thereof to the user interface or the autonomous or semi-autonomous driving system of the first host vehicle.

The disclosure relates generally to an in-vehicle feedback system, and more particularly, to an in-vehicle device with a display or graphical interface that collects driving data and provides feedback based on the driving data. The system may comprise an in-vehicle device that includes a graphical user interface and a processor and a data collection device wirelessly connected to the in-vehicle device. The in-vehicle device may be configured to receive vehicle telematics data from the data collection device and the processor may process the telematics data in real time and cause the telematics data to be displayed on the graphical user interface. The graphical user interface may include a speed display and an acceleration display.

Methods and systems for improving vehicular safety by utilizing uplift modeling techniques to improve a driving tip treatment generation model are provided. According to embodiments, a tip server can analyze telematics data associated with operation of one or more vehicles to determine that a driving tip should be provided to a driver of a vehicle. The tip server then utilize a treatment generation model to determine a treatment for how to provide the driving tip in a manner optimized for the particular driver. The tip server can analyze additional telematics data to determine an effectiveness of the driving tip and to update the treatment generation model in accordance with uplift modeling techniques.

A system for estimating or predicting energy consumption for a trip of a personal vehicle includes a user facing portion and a back-end portion. The user facing portion includes a display and a user interface hosting a real-time application configured to receive travel information and present a received energy distribution via the display. The back-end portion includes a back-end database and an energy processor configured to access the back-end database. The energy processor includes a demand model module configured to produce a set of possible velocity histories and a set of possible ambient temperatures. A vehicle model module is configured to receive the velocity histories and ambient temperatures to provide the energy distribution or a probabilistic prediction of future energy consumption to the user facing portion.