A vehicle judder diagnostic method using artificial intelligence applied to a mobile-based GDS according to the present disclosure is characterized in that the mobile-based GDS samples a plurality of sensor signals of a sensor mounted in a vehicle in a vehicle during operation in a judder evaluation mode to quickly, separately diagnose whether the judder phenomenon of the vehicle is a geometric judder or a friction judder by mounting a deep neural network (DNN) model, developed by the trial and error process of a DNN by using the plurality of sensor signals of a test vehicle mounted with a double clutch transmission (DCT), as a judder determination artificial intelligence model 30 in the mobile-based GDS.

Embodiments of an intelligent hybrid powertrain system include an engine, a controller architecture, and an electric drive subsystem having a battery supply and a motor/generator. The controller architecture is configured to: (i) monitor a current state of charge (SoC) of the battery supply when the combine harvester engages in a combine harvest cycle having a tank fill phase and a tank unload phase; (ii) during the tank fill phase, operate the motor/generator to supplement the engine power output and regulate a rate of battery discharge to prevent the current SoC of the battery supply from decreasing below a lower predetermined SoC threshold prior to completion of the tank fill phase; and (iii) during the tank unload phase, operate the motor/generator to charge the battery supply until the current SoC of the battery supply is equal to or greater than a first upper predetermined SoC threshold.

A fire fighting vehicle includes a chassis, a front axle, a rear axle, an engine, a battery system, an electromagnetic device, an accessory drive, and a controller. The accessory drive is positioned to receive a mechanical input from the engine and the electromagnetic device. The controller is configured to selectively engage a plurality of operational modes including a standby mode and a hybrid mode. According to the standby mode, the controller is configured to operate the electromagnetic device using stored energy stored in the battery system to drive the accessory drive with the engine off. According to the hybrid mode, the controller is configured to operate both the engine and the electromagnetic device.

A system is provided for monitoring spacing during working operation between a first vehicle and at least one further self-propelled vehicle. A beam source is on one vehicle (source vehicle). A sensor arrangement on another vehicle (target vehicle) extends along a sensor axis. In a predetermined reference state, with the vehicles having a predetermined reference spacing apart, the beam source radiates toward the target vehicle electromagnetic radiation such that a predetermined sensor-axial reference detection region on the sensor arrangement is irradiated by the beam source. A change in the vehicle spacing results in a change, along the sensor axis, in the position of the detection region on the irradiated sensor arrangement, and thus in a change in the detection state of the sensor arrangement. Based on the detection state which depends on an actual spacing of the source and target vehicles, a spacing signal is generated with vehicle spacing information.

Excess fuel consumption monitor and feedback systems for vehicles include sensor arrays of two primary types including those sensors deployed as part of a vehicle manufacturer established sensor suite and sensors deployed as after-market sensors. Together, these sensor suites include sensors coupled to vehicle subsystems and operating environments associated with the vehicle. Data from these sensors may be used as parametric inputs to drive algorithmic calculations which have outputs that express excess fuel consumption. Expressions of excess fuel consumption may be made instantaneously as real-time feedback to a vehicle operator/driver and/or a fleet manager as part of a summary report.

A vehicle braking control method is provided. When a driver intends to drive a vehicle after the delivery of the vehicle or a factory mechanic intends to test the vehicle before the delivery of the vehicle after the engine is turned on even when a warning light is turned on due to the insufficiency of the brake fluid, a warning signal indicating that a level sensor is malfunctioning is generated using an instrument cluster, or driving torque of the engine is limited while a warning phrase indicating the insufficiency of the brake fluid is displayed using the cluster. Therefore, the vehicle may travel at a minimum speed. Thus, the driver is enabled to drive the vehicle to a safe place. Accordingly, a secondary accident is prevented and a subsequent maintenance operation is easily performed.

The invention is a method for determining a speed profile for minimizing emissions of at least one pollutant generated by a vehicle during a journey. The method requires a model of the vehicle dynamics, an analytical model of the emissions of the pollutant, and at least one speed profile model divided into at least two phases, each of the phases corresponding to a traction acceleration mode of the vehicle with a number of acceleration modes preferably being five. Then, a speed profile minimizing the emissions of at least one pollutant is determined by seeking, from speed profiles with respect to the distance, duration, and initial and final speeds of the journey and distinguished by distinct phase durations with the speed profile for which the emissions of the pollutant are modelled is by use of an analytical model for which the pollutants are the lowest.

A system for predicting a door opening event of a vehicle includes an identity recognition device associated with an individual occupant profile. The system also includes one or more controllers in electronic communication with the identity recognition device, where the one or more controllers store one or more individual occupant profiles in memory of the one or more controllers that includes historical occupant behavior exhibited by one or more occupants associated with the identity recognition device. The one or more controllers execute instructions to determine a predetermined condition has occurred, where the predetermined condition indicates the vehicle is undergoing a potential engine off event. The one or more controllers determine a door opening event probability value based on at least the gear position probability value and the engine off probability value.

Presented are adaptive operator assistance systems for motor-assisted manually powered (MMP) vehicles, methods for making/using such systems, and electric scooters equipped with such systems. A method of operating an MMP vehicle using a handheld mobile computing device (MCD) includes the handheld MCD receiving path plan data for the MMP vehicle and then receiving, based on this path plan data, MMP-specific ambient data that is aligned with the vehicle's present location and contains surrounding environment data particular to the MMP vehicle. A wireless location device of the handheld MCD tracks the MMP vehicle's real-time location, and a sensing device of the handheld MCD detects MMP-specific threat data that is aligned with the vehicle's real-time location and contains user danger data particular to the MMP vehicle. The handheld MCD then commands a resident subsystem of the MMP vehicle to execute a control operation based on the MMP-specific ambient data and/or threat data.

The present invention relates to a method and device for estimating the road surface friction coefficient of a tire, which estimate the road surface friction coefficient of a tire mounted on a wheel of a vehicle in a state in which the vehicle is normally running at high speed. The method includes: acquiring the state information of a vehicle including at least one of engine state information, transmission state information, and chassis state information from sensors mounted on the vehicle and specifications set for the vehicle; estimating a longitudinal slip ratio, normal force, and longitudinal force for a tire mounted on each wheel of the vehicle by using the acquired state information of the vehicle; and estimating a road surface friction coefficient for the tire by using the estimated longitudinal slip ratio, normal force, and longitudinal force.