CN-121989940-A - Man-machine cooperative driving assisting method and device

CN121989940ACN 121989940 ACN121989940 ACN 121989940ACN-121989940-A

Abstract

The application discloses a man-machine cooperative driving assisting method and device, aiming at the problem that the driving energy efficiency of an electric loader is obviously influenced by the operation of a driver, an accelerator pedal adopts active disturbance rejection optimal acceleration control to reduce energy loss caused by the irregular operation of the driver, and speed sensor data is utilized to combine with a sliding braking strategy to help the driver plan in advance, so that stable parking is realized, and energy waste caused by sudden braking is avoided. The application integrates the operation optimization of the driver and the optimization of the controller, realizes the high-energy-efficiency man-machine collaborative driving, obviously improves the driving energy efficiency of the electric loader, reduces the running cost and simultaneously improves the driving safety and comfort.

Inventors

WANG FENG
LIN ZICHANG
ZHANG HAOXIANG
WU JIAMING
XU BING

Assignees

浙江大学

Dates

Publication Date: 20260508
Application Date: 20260326

Claims (10)

1. The man-machine cooperative driving assisting method is applied to a new energy vehicle and is characterized by comprising the following steps of: S1, acquiring the current depth of an accelerator pedal acquired by an accelerator pedal sensor, determining a target speed according to the current depth of the accelerator pedal, and controlling the new energy vehicle to accelerate to the target speed according to a preset active disturbance rejection optimal acceleration strategy; S2, acquiring the current vehicle speed acquired by the speed sensor, calculating the total braking distance before the vehicle stops according to a preset sliding braking strategy, and displaying the total braking distance.
2. The human-machine cooperative driving assistance method according to claim 1, wherein, The step S1 specifically comprises the following steps: S11, estimating the running resistance of the vehicle according to the current actual vehicle speed acquired by a vehicle speed sensor and the current motor torque fed back by a vehicle motor; S12, fitting the efficiency loss coefficient obtained by adopting a least square method through the motor efficiency historical data of the new energy vehicle; S13, acquiring the current depth of an accelerator pedal acquired by an accelerator pedal sensor, calculating the depth ratio of the current depth of the accelerator pedal to the total depth of the accelerator pedal of the vehicle, and taking the product of the depth ratio and the maximum speed of the new energy vehicle as a target speed; s14, substituting the vehicle running resistance and the efficiency loss coefficient to calculate a motor request torque; And S15, a control instruction corresponding to the motor request torque is sent to the new energy vehicle, and the new energy vehicle is controlled to accelerate to the target speed.
3. The human-machine cooperative driving assistance method according to claim 2, wherein, The step S11 specifically comprises the following steps: according to the current actual vehicle speed acquired by the vehicle speed sensor and the current motor torque fed back by the vehicle motor, estimating the running resistance of the vehicle according to the following formula: ; Wherein, the Representing vehicle speed observation errors, i.e. ; Representing a vehicle speed observation value; representing the current actual vehicle speed acquired by a vehicle speed sensor; Representing an estimated vehicle running resistance; Wherein, the Representing a non-linear filtering function, i.e. ; Wherein, the And Representing gain coefficients, set by experimental data and/or empirical values; And Represents the filter meditation coefficient, is set by experimental data and/or empirical values, represents Filtering boundaries, set by experimental data and/or empirical values; representing the vehicle traction force converted from the current motor torque fed back by the vehicle motor of the new energy vehicle, i.e Wherein, the method comprises the steps of, A current motor torque that is fed back by a vehicle motor representing the new energy vehicle, Representing the radius of the wheels of the new energy vehicle, A motor-to-wheel gear ratio representative of the new energy vehicle; representing a vehicle weight of the new energy vehicle; Wherein, the Representing a sign function, i.e. 。
4. A human-machine cooperative driving assistance method according to claim 3, wherein, The step S12 specifically includes the following steps: s121, acquiring multiple groups of motor efficiency historical data of the new energy vehicle, wherein each group of motor efficiency historical data comprises motor torque, motor rotation speed and motor power loss values under different historical working conditions; s122, carrying the multiple groups of motor efficiency historical data into the following formula, and calculating each efficiency loss coefficient: ; representing the motor torque in the motor efficiency history, Representing the motor speed in the motor efficiency history, 、、、、、 Representing the respective efficiency loss coefficients.
5. The human-machine cooperative driving assistance method according to claim 4, wherein, The step S14 specifically comprises the step of calculating the motor request torque according to the following formula: Wherein, the On behalf of the motor request torque, In a representation of the speed of the object, Representing the current actual vehicle speed acquired by a vehicle speed sensor, Representing the motor-to-wheel gear ratio of the new energy vehicle, Representing the radius of the wheels of the new energy vehicle, Representing a vehicle weight of the new energy vehicle; representing the difference between the target speed and the current actual vehicle speed.
6. The human-machine cooperative driving assistance method according to claim 2, wherein, The step S2 specifically comprises the following steps: S21, acquiring the current vehicle speed acquired by a speed sensor; S22, calculating the sliding distance from the current moment to the preset speed after stopping accelerating according to the following formula: Wherein, the Representing the glide distance; representing the current actual vehicle speed acquired by a vehicle speed sensor; representing the preset vehicle speed, the vehicle speed is determined, , ; Representing acceleration caused by the running resistance of the vehicle during taxiing, i.e. , Representing the estimated running resistance of the vehicle, Representing a vehicle weight of the new energy vehicle; s23, calculating a braking distance from the preset vehicle speed to a stop state according to the following formula: ; Wherein, the Representing the braking distance; Representing the brake average acceleration in the history braking process of the new energy vehicle; And S24, taking the sum of the sliding distance and the braking distance as a braking total distance, and displaying the braking total distance.
7. The human-machine cooperative driving assistance method according to claim 6, wherein, And step S3, acquiring and displaying the target driving distance of the new energy vehicle, and sending out a sliding prompt signal in response to the difference value between the target driving distance and the total braking distance is smaller than a first threshold value.
8. The human-machine cooperative driving assistance method according to claim 7, wherein, And step S3, a braking prompt signal is sent out in response to the difference value between the target driving distance and the braking distance is smaller than a second threshold value, wherein the braking distance is the forward moving distance from the preset speed to the stopping state of the new energy vehicle.
9. The human-machine cooperative driving assistance method according to claim 7 or 8, wherein, The target driving distance comprises a front obstacle distance acquired by a front radar of the new energy vehicle or a driving distance between the current position of the new energy vehicle and the target ground position.
10. A man-machine cooperative driving assisting device is characterized in that, Comprising a processor, an input device, an output device and a memory, the processor, the input device, the output device and the memory being interconnected, wherein the memory is adapted to store a computer program comprising program instructions, the processor being configured to invoke the program instructions to perform the method according to any of claims 1 to 9.

Description

Man-machine cooperative driving assisting method and device Technical Field The application relates to the technical field of display panels, in particular to a man-machine collaborative auxiliary driving method and device. Background Under the background of the vigorous development of new energy technology, the electric loader is widely applied to the fields of mines, buildings, logistics and the like as a representative of green construction equipment. The energy-saving and emission-reducing system takes electric power as driving, realizes zero emission or low emission, effectively reduces the dependence on traditional fossil energy sources, and accords with the global trend of energy conservation and emission reduction and sustainable development. However, the running energy efficiency of the electric loader is significantly affected by the driving operation of the driver. Because the drivers are uneven in level, irregular operations such as sudden acceleration and sudden braking often occur in the driving process, and the motor is often operated in a low-efficiency area due to the difference of the power characteristic and the energy consumption characteristic of the electric loader and the traditional fuel loader, so that the driving energy efficiency is seriously influenced. In addition, the mismatch of the conventional driving habits of the driver with the electric loader further exacerbates the loss of energy efficiency. Disclosure of Invention The application aims to provide a man-machine cooperative driving assisting method and device, which can solve the problems. Embodiments of the present application are implemented as follows: In a first aspect, the present application provides a method for assisting driving with human-computer collaboration, which includes steps S1 to S2, wherein S1, S2, etc. are only step identifiers, and the execution sequence of the method is not necessarily performed in the order from small to large, for example, step S2 may be performed first and then step S1 may be performed, which is not limited by the present application. S1, acquiring the current depth of an accelerator pedal acquired by an accelerator pedal sensor, determining a target speed according to the current depth of the accelerator pedal, and controlling the new energy vehicle to accelerate to the target speed according to a preset active disturbance rejection optimal acceleration strategy; S2, acquiring the current vehicle speed acquired by the speed sensor, calculating the total braking distance before the vehicle stops according to a preset sliding braking strategy, and displaying the total braking distance. It will be appreciated that in step S1, the system determines the driver' S acceleration intention and target speed by acquiring real-time data of the accelerator pedal sensor. Based on the depth information, the system adopts an active disturbance rejection optimal acceleration strategy to intelligently regulate and control the output of the motor, so that the new energy vehicle is stably accelerated to a target speed. The strategy can effectively resist external interference, ensure smoothness and high efficiency of the acceleration process, and promote driving experience. Step S2 focuses on driving safety and distance management. The system monitors the current speed by utilizing a speed sensor, and accurately calculates the total braking distance from the current speed to complete stopping of the vehicle by combining a preset sliding braking strategy. The distance information is displayed on the driving interface in real time, visual parking reference is provided for a driver, braking operation is planned in advance, parking safety and accuracy are guaranteed, energy utilization is optimized, and energy waste caused by unnecessary sudden braking is reduced. In an alternative embodiment of the present application, the step S1 specifically includes the following steps S11 to S15, where S11, S12, etc. are only step identifiers, and the execution sequence of the method is not necessarily performed in the order from small to large, for example, the step S12 may be performed first and then the step S11 may be performed, which is not limited by the present application. S11, estimating the running resistance of the vehicle according to the current actual vehicle speed acquired by the vehicle speed sensor and the current motor torque fed back by the motor of the vehicle. S12, fitting the efficiency loss coefficient obtained by the least square method through the motor efficiency historical data of the new energy vehicle. S13, acquiring the current depth of the accelerator pedal acquired by an accelerator pedal sensor, calculating the depth ratio of the current depth of the accelerator pedal to the total depth of the accelerator pedal of the vehicle, and taking the product of the depth ratio and the maximum speed of the new energy vehicle as a target speed. S14, carrying the vehicle running resistance and