240results about "Data processing management" patented technology

A method for controlling a vehicle on a mission, the vehicle comprising a first and a second power source for driving the vehicle itself, wherein the first power source comprises an engine configured to generate power from fuel and an after treatment system coupled to the combustion engine, the method comprising the steps of solving a convex first optimal control problem based on a mathematical model of the vehicle, the first optimal control problem involving state variables for the after treatment system, a set of constraints, and a cost function having control variables that include a discrete variable and a continuous variable; the solving including an initial determination of the discrete variable and an iterative execution of minimizing the cost function after replacement of the discrete variable with respect to the continuous variable, updating the discrete variable, and verifying the satisfaction of a convergence criterion.

The invention provides a ramp energy-saving control method based on off-line speed planning and dual-mode model prediction tracking, and aims to solve the problems of insufficient precision of ramp driving energy consumption and safety cooperative control and frequent mode switching of an automatic driving vehicle. The method comprises the following steps: firstly, identifying a key road section based on high-precision road gradient data, and generating an optimal energy-saving reference speed matched with gradient characteristics in an off-line manner by adopting a dynamic planning and sequential quadratic planning hybrid optimization strategy; secondly, when the vehicle runs, relevant information is loaded after confirmation of a driver, the system takes over the longitudinal control right, two control modes are dynamically switched based on the front vehicle distance, and frequent mode switching is avoided through a hysteresis threshold value; and finally, taking the slope-fused vehicle longitudinal dynamics model as a prediction model, solving an optimal control instruction online by adopting a model prediction control algorithm, performing closed-loop execution, monitoring intervention operation of a driver, and immediately returning the driving right after the intervention operation is detected. According to the method, offline planning and online dual-mode tracking technologies are integrated, the method has the advantages of high energy consumption optimization precision, stable mode switching and good safety adaptability, and energy-saving and safe driving of the automatic driving vehicle in a ramp scene is realized.

The method is mainly applied to the technical field of vehicle engineering. The invention discloses a combined driving assistance vehicle driving control method, system and device and a medium. The method comprises the steps that running state information of a vehicle and traffic state information of the position where the vehicle is located are obtained; generating a driving path for guiding the vehicle to pass through the traffic signal prompt area according to the traffic state information, and determining the speed of the vehicle when the vehicle runs on the driving path; inputting the running state information and the vehicle speed into a preset energy consumption characteristic model, and determining the energy consumption of the vehicle when the vehicle runs on the running path through the energy consumption characteristic model; and generating a control instruction set based on the driving path, the vehicle speed and the energy consumption, and controlling the vehicle to execute driving operation according to the control instruction set. According to the invention, through the combined decision and the driving assistance control operation, the driving intelligence is obviously improved.

The invention discloses a commercial vehicle energy-saving control method based on expected vehicle speed prediction, aims to improve the energy-saving effect of a commercial vehicle at the expected vehicle speed of a driver, and specifically comprises the following steps: (1) carrying out vehicle longitudinal dynamics modeling; (2) establishing a commercial vehicle fuel consumption model; and (3) establishing an objective function which considers the ability of tracking the expected speed of the driver, the energy-saving effect of the vehicle and the torque change of the vehicle, solving a multi-objective optimization problem by using model predictive control, and designing constraint conditions. And finally, the economic level of the commercial vehicle is improved on the premise of reasonably tracking the expected vehicle speed of the driver.

The invention relates to the technical field of automobiles, and particularly provides a heavy-duty automobile cruise control method, system and device and a storage medium, and the method comprises the steps: obtaining real-time road condition information and vehicle operation data through the fusion of a vehicle-mounted sensor and a driving assistance map; predicting a future vehicle weight, and predicting a future road adhesion coefficient based on the vehicle operation data and the historical road adhesion coefficient data; constructing a state variable based on the real-time road condition information, the vehicle operation data and the road adhesion coefficient, and defining a control variable; establishing a cost function including a safety item, a fuel saving item and a stability item, and setting constraint conditions of a vehicle state variable and a control variable; based on a dynamic programming algorithm, solving a minimum value of a cost function under the condition of satisfying constraint conditions, and obtaining an optimal control variable sequence; and according to the optimal control variable sequence, the gear, the driving torque and the braking torque of the vehicle are adjusted. Through multi-source information fusion and layered dynamic planning, the cruise control performance of the heavy-duty car is remarkably improved.

The invention relates to the technical field of ecological driving, in particular to a self-adaptive ecological cruise method and device based on dynamic vehicle behavior prediction.The method comprises the steps that on the basis of at least one driving parameter of a surrounding vehicle within a vehicle target range, the transverse motion state of the surrounding vehicle is recognized, predicting a dynamic driving track of the surrounding vehicle in the future target time according to the transverse motion state; in combination with the at least one driving parameter and the dynamic driving track, generating a vehicle distance variation between the surrounding vehicles in the future target time; and generating a self-adaptive ecological cruise strategy of the vehicle at the current moment based on the dynamic driving track, the vehicle distance variation and a preset driving constraint condition. Therefore, the problems that the prediction dimension of the ecological cruise control strategy of the new energy automobile is still limited to the longitudinal motion state change, the decision complexity of the new energy automobile as an intelligent driving main body is ignored, and obvious insufficient environmental adaptation is achieved in a dynamic traffic scene in the related technology are solved.

The invention belongs to the technical field of vehicle control, and particularly relates to a high-speed scene automatic driving performance analysis method and system for a heavy-duty commercial vehicle, and the method comprises the steps: synchronously collecting the current positioning data, camera image data, vehicle bus signals and inertial navigation data of the heavy-duty commercial vehicle in an automatic driving process in a high-speed scene; generating a transverse track, a longitudinal track and an oil consumption time sequence data set which are in space-time alignment based on the collected data; a three-in-one evaluation system of transverse safety, longitudinal response and fuel economy is constructed by calculating transverse safety margin and lane centering stability in the step S2, calculating longitudinal response delay and aging deviation in the step S3 and fuel consumption deviation per hundred kilometers in the step S4. And each dimension is quantified through a clear formula, so that the evaluation result is traceable and reproducible, and the comprehensive performance of the automatic driving system in a high-speed scene is comprehensively reflected.

An electrified vehicle and associated method for controlling an electrified vehicle having an electric machine powered by a traction battery include an autoencoder trained with training data indicative of a remaining driving range of the traction battery. The trained autoencoder processes vehicle operating data to generate a reference data record and determines a value indicative of a similarity between the vehicle operating data and the reference data record. The autoencoder generates an output data record if the value indicative of the similarity is below a predetermined threshold value. The output data record may be used to display an alert or message to a vehicle occupant and / or control the vehicle to reduce power consumption to increase vehicle driving range.

The invention relates to the technical field of engine oil consumption control, in particular to an oil-saving control method and system based on the cooperative game theory and behavior analysis and a vehicle. The method comprises the following steps: determining N driving behavior characteristics according to driving behavior data; inputting the driving behavior characteristics into an oil consumption prediction model, and predicting to obtain an oil consumption prediction value; and calculating the marginal contribution degree and the fuel-saving potential coefficient corresponding to each driving behavior characteristic, and determining the fuel-saving potential value of each driving behavior characteristic according to the marginal contribution degree and the fuel-saving potential coefficient. According to the method, the complex nonlinear relation between the driving behaviors and the fuel consumption is captured through the machine learning model, the marginal contribution degree of each driving behavior to the fuel consumption is determined through the Shapley value, and then the fuel-saving potential value of each driving behavior is determined. And providing targeted driving suggestions for each driving behavior of the driver according to the fuel-saving potential value.

An energy-saving vehicle speed planning method, system, electronic device, and storage medium. The method comprises: obtaining a vehicle's current speed and current acceleration; obtaining slope information and spacing information for multiple sub-segments in a target road segment ahead of the vehicle, each sub-segment having a unique slope; calculating, based on the current speed, current acceleration, slope information, and spacing information, a predicted vehicle speed and predicted travel time in each sub-segment under a constant power output; calculating a predicted average speed for the target road segment, and calculating a speed difference between the predicted average speed and a target speed for passing the target road segment; and generating a first planned speed for the vehicle in each sub-segment based on the speed difference and the predicted vehicle speed. The speed planning calculation for the target road segment is highly efficient.

A collision detection method, an electronic device, and a storage medium are provided, which relate to a field of artificial intelligence technology, and in particular to fields of intelligent transportation and autonomous driving technologies. The method includes: determining a predicted travel range of a target object based on a planned travel trajectory of the target object and a historical travel trajectory of the target object; determining, in response to a target obstacle being detected, a predicted travel range of the target obstacle based on a current travel state of the target obstacle; and determining whether the target object has a risk of colliding with the target obstacle, based on the predicted travel range of the target object and the predicted travel range of the target obstacle.

The application provides a driving style recognition method and device, comprising: acquiring vehicle driving data at a current time; determining whether the vehicle driving data at the current time is valid data affecting driving style; in response to the vehicle driving data at the current time being valid data, determining a driving style index value at the current time based on the vehicle driving data at the current time; determining a driving style quantitative value at the current time based on the driving style index value at the current time and a driving style index value at a historical time; in response to the vehicle driving data at the current time not being valid data, determining the driving style quantitative value at the current time based on the driving style index value at the historical time; and determining the driving style at the current time based on the driving style quantitative value at the current time. The method can realize real-time recognition of the driving style of a driver, and the accuracy of the recognition result and the efficiency of the recognition are relatively high.

Procedures for controlling an electric vehicle, which include the following: Changing the operation of an electric vehicle in response to a predicted energy consumption value; characterized in that the method further comprises the following: Adjusting the predicted energy consumption in response to a standard deviation of fluctuations in past energy consumption values ​​(R); and Reducing a predicted remaining range (DTE) in a non-linear manner using the adjusted predicted energy consumption as a battery state of charge (BSOC, CSOC) decreases, where the predicted energy consumption value X is calculated using the following equation (1): X = μ+ z'* σ , where µ is the mean energy consumption value during a driving cycle, σ is the standard deviation of the energy consumption value during the driving cycle, and z' is a weighting factor of σ.

To provide a work vehicle capable of improving fuel economy by the control to switch modes between an economy mode and a standard mode at an appropriate timing, and capable of eliminating the troublesomeness of manually switching the modes between the standard mode and the economy mode.SOLUTION: A work vehicle 1 includes an engine 20, a first hydraulic pump 31, a second hydraulic pump 32, a travelling device 6, a work device 9, an operation device 5, an ECU 30, and a vehicle controller 7. The vehicle controller 7 transmits a control command in a standard mode to the ECU 30 when the travelling device 6 is stopped, discharge pressure from the second hydraulic pump 32 is a reference value U1 or more, and a first period T1 passes with an engine load factor of a predetermined upper limit E1 or more, transmits a control command in an economy mode to the ECU 30 when a second period T2 passes with the engine load factor of a predetermined lower limit or less, and transmits a control command in the standard mode to the ECU 30 when the travelling device 6 is actuated.SELECTED DRAWING: Figure 1

To provide an on-vehicle display device that allows a user to improve fuel consumption depending on efforts made in driving.SOLUTION: An on-vehicle display device includes: an environment data acquisition part for acquiring travel environment data of a route on which a vehicle is scheduled to travel; past travel data acquisition means for acquiring, as past average fuel consumption data, average fuel consumption for the route, on the basis of a travel history of the vehicle and the travel environment data; predicted travel data acquisition means for acquiring, as predicted average fuel consumption data, average fuel consumption for the route, on the basis of a travel status of the vehicle and the travel environment data; average fuel consumption comparison means for comparing the past average fuel consumption data with the predicted average fuel consumption data to determine good / poor of the fuel consumption; and display-presentation means for presenting a display of travel status with respect to the route, a display of good / poor of the fuel consumption of the predicted average fuel consumption data with respect to the past average fuel consumption data, and, when the fuel consumption of the predicted average fuel consumption data is poor with respect to the past average fuel consumption data, a display of operation that may improve the fuel consumption of the predicted average fuel consumption data with respect to the route.SELECTED DRAWING: Figure 2

To provide a work vehicle capable of improving fuel economy by the control to switch modes between an economy mode and a standard mode at an appropriate timing, and capable of eliminating the troublesomeness of manually switching the modes between the standard mode and the economy mode.SOLUTION: A work vehicle 1 includes an engine 20, a first hydraulic pump 31, a second hydraulic pump 32, a travelling device 6, a work device 9, an operation device 5, an ECU 30, and a vehicle controller 7. The vehicle controller 7 transmits a control command in a standard mode to the ECU 30 when the travelling device 6 is stopped, discharge pressure from the second hydraulic pump 32 is a reference value U1 or more, and a first period T1 passes with an engine load factor of a predetermined upper limit E1 or more, transmits a control command in an economy mode to the ECU 30 when a second period T2 passes with the engine load factor of a predetermined lower limit or less, and transmits a control command in the standard mode to the ECU 30 when the travelling device 6 is actuated.SELECTED DRAWING: Figure 1

A fleet management system dispatches autonomous electric vehicles (AEVs) as on-demand power sources. The fleet management system receives a request for a power source including a location and data describing the amount of power requested. The fleet management system selects an AEV of the fleet to service the request based on the relative locations of the AEVs to the requested location, and based on the amount of power requested. The fleet management system instructs the selected AEV to drive to the location and supply power. The fleet management system instructs the selected AEV to disconnect and return to the charging station, and may instruct another AEV to continue fulfilling the request if additional power is needed.

The application relates to the technical field of vehicles and discloses a driving behavior processing method, device and equipment and a storage medium, the method comprising the following steps: acquiring current driving data of a vehicle and current road data of a driving road of the vehicle; determining index data corresponding to each driving index according to the current driving data and the current road data; calculating index scores of the driving indexes according to the index data; when it is determined that a user has an abnormal driving behavior according to the index scores of the driving indexes, processing the abnormal driving behavior; in the above manner, the index scores of the driving indexes are calculated by using the index data, and it is determined whether the user has an abnormal driving behavior according to the index scores of the driving indexes; if yes, the abnormal driving behavior is processed, so that the accuracy of determining the abnormal driving behavior can be effectively improved, and the abnormal driving behavior can be processed in time, so that the driving safety is improved.

Data is collected regarding at least one of a coolant temperature of a vehicle, an atmospheric ozone level, and an air quality. A refueling time is determined based on the collected data. The vehicle is moved to a refueling station based on the refueling time.

A driver assist apparatus includes one or more processors configured to: collectively provide instructions of settings with group, the settings being set to driver assist functions included in the group, and the group being configured so that the driver assist function of a vehicle is allowed to be added to or deleted from the group; and when a specific group that is a driving mode to suppress fuel consumption is selected from among the groups, change settings corresponding to suppression of fuel consumption of the vehicle in a plurality of the driver assist functions, included in the specific group.

Method for operating a powertrain system comprising a multi-mode transmission designed to transmit torque between a power machine, torque machines and a final drive, the method comprising: Determining an objective function for a target component of interest; Identifying constraints for a plurality of independent and dependent variables; Evaluating a plurality of permutations of the objective function based on the independent variables and the dependent linear variables; Evaluate the objective function to determine maximum and minimum values ​​for the objective function for each of the permutations; Determining overall minimum and maximum values ​​for the objective function based on the maximum and minimum values ​​for the objective function for each of the permutations; and Controlling the operation of the powertrain system to which the target component of interest is assigned, based on the overall minimum and maximum values ​​for the objective function.

The present invention relates to a method for implementing an EV (electric vehicle) ecosystem and a device for performing such a method. The method for implementing an EV (electric vehicle) ecosystem includes the steps of: an EV ecosystem management device receiving EV eco-data from EV ecosystem participants; and the EV ecosystem management device managing the EV eco-system based on the EV eco-data.

A method for controlling a gear change in response to a change in a driving mode, the method comprising: (a) determining a maximum number of permissible low gearshift steps according to a result of determining a state of a transmission based on information about an accelerator pedal operation (a signal from an accelerator pedal position sensor (APS; 20)) when a request to change a driving mode to a sport mode is detected during driving, (b) calculating a turbine wheel speed expected immediately after the gear change for each stage included in the maximum number of permissible low gear shift stages using a current speed of an output shaft of the transmission and a gear ratio of each stage, and comparing the calculated expected turbine wheel speed (a speed of an input shaft of the transmission) with a preset permissible turbine wheel speed for each stage, (c) setting the lowest gear shift step from gear shift steps for which the expected turbine speed and the permissible turbine speed satisfy a predetermined condition, such that it is a target gear shift step within the maximum number of permissible low gear shift steps, and (d) executing a gear shift control to downshift a current gear shift stage to the target gear shift stage, wherein in (a) determining the maximum number of permissible low gearshift steps, if an output signal of an APS (20) is at or above a set value at a time when the request to change the driving mode is detected, it is determined that the transmission is in an engaged state, and if the output signal of the APS (20) is below the set value, it is determined that the transmission is in a disengaged state, wherein, when the transmission is in the engaged state, the number of low gearshift steps lower than a set gearshift step determined via a gearshift pattern associated with a sport mode is determined as the maximum number of permissible low gearshift steps, and when the transmission is in the disengaged state, the maximum number of permissible low gearshift steps is determined as 1, such that a low gearshift is only possible to a low gearshift step (a set gearshift step number minus 1) that is one step lower than the set gearshift step determined via the gearshift pattern associated with the sport mode.

This invention discloses an energy-saving optimization control method for vehicle-mounted terminals, specifically relating to the field of energy-saving optimization control technology. It involves collecting real-time operating condition data and real-time power consumption status data of the vehicle-mounted terminal, preprocessing and extracting features to generate operating condition switching feature data and real-time power consumption feature data of the terminal; analyzing the switching speed characteristics of vehicle operating conditions to generate switching speed levels for vehicle operating conditions; analyzing the response delay characteristics of different energy-saving control strategies to generate response delay levels for energy-saving control strategies; jointly analyzing the switching speed levels of vehicle operating conditions and the response delay levels of energy-saving control strategies to generate time-series mismatch data; analyzing the occurrence conditions and duration of energy efficiency inversion phenomena to generate time-domain risk data of energy efficiency inversion, and dynamically adjusting the pre-triggering timing and response speed of energy-saving control strategies; thereby improving the accuracy of energy-saving response and control robustness during vehicle operation.

The invention provides a vehicle driving strategy information generation method and device and electronic equipment, and relates to the technical field of vehicles. The method comprises the following steps: acquiring driving data of automatic variable-speed driving of a vehicle; extracting driving style information from the driving data; based on the driving style information, vehicle driving strategy information used for reducing energy consumption is generated for a plurality of driving styles corresponding to the driving style information, and the vehicle driving strategy information comprises power parameters of an execution vehicle. According to the method and the device, different vehicle driving strategy information is generated according to different driving styles through the driving style information, so that the power parameters in the strategy information are applied in the driving process to achieve an energy-saving effect.

The present invention provides a method, apparatus, vehicle, medium, and equipment for determining the optimal economic operating point of a hybrid vehicle. The method includes: obtaining actual operating parameters and equivalent fuel consumption power corresponding to the vehicle at a current operating point; determining the most economical operating point of the vehicle under different driving modes and the optimal equivalent fuel consumption power corresponding to the most economical operating point based on the actual operating parameters of the vehicle at the current operating point; and determining the optimal economic operating point of the hybrid vehicle based on the optimal equivalent fuel consumption power corresponding to the most economical operating point of the vehicle under different driving modes and the equivalent fuel consumption power corresponding to the vehicle at the current operating point.

Device for providing eco-driving information for a vehicle, comprising: a vehicle weight calculation unit (1) which is configured to calculate a current weight of the vehicle based on data received from a plurality of devices within the vehicle; a computing unit (3) for the electrical load, which is equipped to calculate an electrical load of auxiliary machines currently used in the vehicle; a vehicle speed calculation unit (5) configured to calculate, using a route map, a fuel-efficiency-oriented vehicle speed that maximizes the vehicle's travel distance according to the calculated vehicle weight and electrical load; and a display device (7) which is set up to display the calculated fuel efficiency-oriented vehicle speed to a user. where the weight of the vehicle is calculated from the electricity consumption of a vehicle drive motor, an air density, a drag coefficient, a projection area of ​​the vehicle, the vehicle speed, a coefficient of friction of a current road on which the vehicle is traveling, the acceleration due to gravity and an inclination of the current road on which the vehicle is traveling, where the weight of the vehicle is calculated using the following equation m = ( TF + 1 2 ρ air C d AV 2 ) / ( μ g cos θ+ g sin θ ) where m represents vehicle weight, TF represents a driving force, ρ air which represents air density, C da drag coefficient, A a projection area of ​​the vehicle, V the vehicle speed, µ a coefficient of friction of the current road, g the acceleration due to gravity of the vehicle, and θ the current inclination of the road, and The driving force is obtained from a relationship TF = P / V, where P represents the power input of the drive motor and V represents the vehicle speed. wherein the vehicle weight calculation unit (1), the electrical load calculation unit (3) and the vehicle speed calculation unit (5) are incorporated into a single chip and the route map comprising the vehicle weight, electrical load and vehicle speed is embedded in the chip.

This invention relates to an autonomous driving control method, device, electronic device, and computer storage medium, belonging to the field of autonomous driving technology. The autonomous driving control method includes acquiring scene information of the vehicle's location, including vehicle state information and road environment information of the road where the vehicle is located; analyzing the vehicle state information and road environment information using a deep reinforcement learning-based vehicle energy-saving control model to determine a vehicle control strategy. The vehicle energy-saving control model includes a reward function, which represents the balance between safe driving and energy efficiency under the vehicle control strategy, with the reward function corresponding to the vehicle control strategy having the maximum reward value; and controlling the vehicle to drive autonomously according to the vehicle control strategy. This invention can effectively reduce vehicle energy consumption and save energy.

This application provides a vehicle control method, device, vehicle, storage medium, and program product, relating to the field of vehicle technology. The method includes: acquiring vehicle information and, based on the vehicle information and a preset speed limit, determining whether to send a command to limit engine torque. The vehicle information includes the current engine speed and torque, vehicle speed prediction data, and torque prediction data. By analyzing the data of the above types of information, and reasonably limiting engine torque, the vehicle's fuel efficiency can be improved.

This application relates to the field of computer technology and provides a vehicle control method, device, electronic device, and medium. The method includes: upon detecting a vehicle control transfer operation targeting a target vehicle, generating a control transfer request to request the transfer of vehicle control, wherein the control transfer request includes vehicle description information describing the current state of the target vehicle; sending the control transfer request to a target authorized terminal; receiving a driving control command sent by the target authorized terminal based on the control transfer request; and controlling the target vehicle to drive according to the driving control command. This application enables a timely transfer of vehicle control to a user at a target authorized terminal when the driver is in poor condition. The user at the target authorized terminal can then remotely control the vehicle based on its current state, preventing drivers from driving in poor condition and helping to reduce traffic safety hazards.