A method, device, equipment and medium for recovering energy from a vehicle going downhill

Abstract

The present invention discloses a method, device, equipment, and medium for vehicle downhill energy recovery. The method comprises: when determining that the vehicle is traveling smoothly downhill, calculating the current integrated value and convergence variance of the variable parameters based on the acquired integrated value and convergence variance of the variable parameters at the previous moment and the real-time vehicle data collected at the current moment; when it is determined that the convergence conditions are met based on the current integrated value and convergence variance of the variable parameters, determining the current integrated value of the variable parameters as the target integrated value; calculating the target torque based on the target integrated value and the real-time vehicle data collected at the current moment; and controlling the energy recovery force based on the target torque. Embodiments of the present invention can improve the adaptability of vehicle downhill energy recovery.

Description

Technical Field

[0001] The present invention relates to the field of vehicle control technology, and in particular to a method, device, equipment and medium for recovering energy from a vehicle going downhill. Background Art

[0002] With the rapid development of new energy vehicles, vehicle downhill energy recovery technology has been widely used in new energy vehicles. Vehicle downhill energy recovery technology uses the gravitational potential energy of the vehicle going downhill to convert the kinetic potential energy into electrical energy, thereby realizing energy recovery and reuse.

[0003] Currently, new energy vehicles achieve downhill energy recovery based on a fixed energy recovery level.

[0004] However, a fixed energy recovery level will cause the vehicle to be unable to adapt to different slopes, resulting in a poor driving experience. Summary of the Invention

[0005] The present invention provides a method, device, equipment and medium for recovering energy when a vehicle is going downhill. The embodiments of the present invention can improve the adaptability of energy recovery when a vehicle is going downhill.

[0006] In a first aspect, an embodiment of the present invention provides a method for recovering energy from a vehicle going downhill, the method comprising:

[0007] When determining that the vehicle is traveling steadily downhill, the integrated value of the change parameter and the convergence variance at the current moment are calculated based on the integrated value of the change parameter and the convergence variance obtained at the previous moment and the real-time data collected by the vehicle at the current moment;

[0008] When it is determined that the convergence condition is met according to the integrated value of the change parameter at the current moment and the convergence variance, the integrated value of the change parameter at the current moment is determined as the target integrated value;

[0009] Calculate the target torque based on the target integrated value and the current real-time vehicle data;

[0010] Controls energy recovery strength according to target torque.

[0011] In a second aspect, an embodiment of the present invention further provides a vehicle downhill energy recovery device, the device comprising:

[0012] A change parameter integration value calculation module is used to calculate the change parameter integration value and convergence variance at the current moment based on the acquired change parameter integration value and convergence variance at the previous moment and the real-time vehicle data collected at the current moment when determining that the vehicle is traveling steadily downhill;

[0013] a target integrated value determination module, configured to determine the integrated value of the changing parameter at the current moment as the target integrated value when it is determined that the convergence condition is met based on the integrated value of the changing parameter at the current moment and the convergence variance;

[0014] The target torque calculation module is used to calculate the target torque based on the target integration value and the real-time collected data of the vehicle at the current moment;

[0015] The energy recovery control module is used to control the energy recovery force according to the target torque.

[0016] In a third aspect, an embodiment of the present invention further provides a vehicle downhill energy recovery device, the vehicle downhill energy recovery device comprising:

[0017] at least one processor; and

[0018] a memory communicatively connected to at least one processor; wherein,

[0019] The memory stores a computer program that can be executed by at least one processor. The computer program is executed by the at least one processor so that the at least one processor can execute the vehicle downhill energy recovery method according to any embodiment of the present invention.

[0020] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable a processor to implement the vehicle downhill energy recovery method of any embodiment of the present invention when executed.

[0021] The technical solution of the embodiment of the present invention makes the vehicle's estimation of the current state during the downhill process more stable and accurate through the integrated value and convergence variance of the changing parameters at the previous moment; by judging the convergence conditions, the vehicle can determine the target integrated value when the changing parameters tend to be stable, ensuring that the target integrated value is each single changing parameter close to the actual integrated value of the changing parameters; using the target integrated value and the real-time collected data of the vehicle to calculate the target torque, it can be ensured that the vehicle's downhill energy recovery is adapted to the current speed, slope and other driving parameters, thereby optimizing the energy recovery efficiency; by controlling the energy recovery force according to the target torque, the energy recovery intensity is adjusted in real time, and a fine control method is implemented, which can effectively recover energy during the vehicle's smooth descent, while avoiding excessive deceleration or insufficient deceleration, thereby improving driving comfort and safety.

[0022] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 This is a flow chart of a vehicle downhill energy recovery method provided by an embodiment of the present invention;

[0025] Figure 2 This is a flow chart of a vehicle downhill energy recovery method provided by an embodiment of the present invention;

[0026] Figure 3 2. It is a structural diagram of a vehicle downhill energy recovery device provided according to an embodiment of the present invention;

[0027] Figure 4 The figure is a schematic structural diagram of a vehicle downhill energy recovery device provided according to an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0030] In the technical solutions of the embodiments of the present invention, the acquisition, storage and application of real-time vehicle data, etc., are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0031] Figure 1This is a flow chart of a vehicle downhill energy recovery method provided by an embodiment of the present invention. This embodiment of the present invention is applicable to situations where a vehicle is recovering energy while downhill. The method can be performed by a vehicle downhill energy recovery device, which can be implemented in hardware and / or software.

[0032] See also Figure 1 The vehicle downhill energy recovery method shown includes:

[0033] S101. When determining that the vehicle is traveling steadily downhill, calculate the integrated value of the change parameter and the convergence variance at the current moment based on the acquired integrated value of the change parameter and the convergence variance at the previous moment and the real-time vehicle data collected at the current moment.

[0034] The integrated value of a variable parameter can be an estimated value of the integrated value of a variable parameter that cannot be obtained by sensors. It can be an estimated value of the integrated value obtained by integrating and calculating the relevant variable parameters of the vehicle's longitudinal dynamics. For example, the integrated value of a variable parameter can be an estimated value derived from the combined value of the load weight, volume, and shape. There are multiple variable parameters, including transmission efficiency, tire radius, vehicle mass, drag coefficient, air density, frontal area, vehicle relative speed, ambient wind speed, and rolling resistance coefficient. The collected data cannot accurately determine the precise value of a single variable parameter. Only an estimated value of a relationship formula combining these parameters can be determined. This estimated value of the relationship formula is the integrated value of the variable parameter. Because the values ​​of individual parameters are affected by various factors, for example, slight deformation of the tire during driving due to load, temperature, and speed results in a variable tire radius. The integrated value of the unobtainable variable parameter can be estimated based on the available parameter values, resulting in an approximate estimate of the actual parameter, but not the exact value. The parameter values ​​that can be obtained include motor torque, gear ratio of the transmission, main reduction ratio, actual vehicle speed and longitudinal acceleration.

[0035] Among them, the real-time vehicle status data may refer to the relevant numerical values ​​of the current driving state of the vehicle collected by sensors and controllers. The real-time vehicle status data may include data such as motor torque, gear ratio of the transmission, main reduction ratio, actual vehicle speed and longitudinal acceleration. The real-time vehicle status data is used to provide accurate and true input values ​​for the vehicle longitudinal dynamics model to help estimate parameters that cannot be directly measured. For example, the longitudinal acceleration can be obtained by the acceleration sensor, the motor torque can be obtained by the motor controller, and the actual vehicle speed can be obtained by the vehicle speedometer. That is, the real-time data obtained in the above manner may refer to the real-time vehicle status data.

[0036] S102 : When it is determined that the convergence condition is satisfied based on the integrated value of the change parameter at the current moment and the convergence variance, the integrated value of the change parameter at the current moment is determined as the target integrated value.

[0037] Among them, the convergence condition may refer to a standard for judging whether the estimated integrated value of the changing parameters has reached a stable state. The convergence condition is used to ensure that the error between a single changing parameter in the estimated integrated value of the changing parameters and the actual changing parameter is small. Exemplarily, the convergence condition may refer to determining that the integrated value of the changing parameters at the current moment is determined as the target integrated value when the error between the estimated longitudinal acceleration and the true acceleration is less than a preset error threshold and the forgetting coefficient is greater than a preset coefficient threshold. For example, when the mean error between the estimated longitudinal acceleration and the true acceleration is less than 0.01 and the forgetting coefficient is greater than 0.999, determining that the integrated value of the changing parameters at the current moment is determined as the target integrated value, and using the target integrated value as the optimal parameter of the longitudinal dynamics model of the whole vehicle.

[0038] The target integrated value can refer to the integrated value of the variable parameters when the convergence condition is met. When the convergence condition is met, the integrated value of the variable parameters under that condition is determined as the target integrated value, which can be considered the vehicle dynamics parameter that best represents the current vehicle driving state. The target integrated value serves as the basis for calculating the target torque, providing the closest estimate to the actual vehicle dynamics parameter, making subsequent calculations more accurate.

[0039] S103 : Calculate the target torque based on the target integrated value and the current real-time collected vehicle data.

[0040] The target torque refers to the motor braking torque required to maintain zero vehicle acceleration. The target torque is calculated using the vehicle longitudinal dynamics equation based on the target integration value and real-time vehicle data. The target torque value determines whether to enable downhill energy recovery. When the target torque is positive, energy recovery is disabled, while when it is negative, energy recovery is enabled, achieving stable vehicle braking force.

[0041] In a specific example, ideally, when the vehicle acceleration is zero, the vehicle speed remains constant to avoid a poor driving experience caused by repeated changes in vehicle speed. Substituting the vehicle acceleration equal to zero into the vehicle dynamics formula, the target torque can be calculated using the following formula:

[0042]

[0043] Where T represents the target torque, v1 represents the actual vehicle speed, and x1, x2, x3, and x4 represent the target integrated values.

[0044] S104: Control the energy recovery force according to the target torque.

[0045] Among them, the energy recovery strength may refer to the strength of controlling the energy recovery of the vehicle when going downhill. The energy recovery strength reflects the degree of influence of motor braking on energy recovery. The strength of the energy recovery strength depends on the numerical value of the target torque, and the energy recovery strength can be determined according to the specific numerical value of the target torque. By controlling the energy recovery strength, it is possible to avoid vehicle instability caused by excessive energy recovery strength, maintain a stable speed and state when going downhill, and improve driving comfort and energy recovery efficiency. For example, when the target torque is negative, the vehicle performs downhill energy recovery, and the energy recovery strength can be determined according to the absolute value of the torque, based on the energy recovery strategy set in advance. For example, when the absolute value of T is in the XY interval, it indicates that the current braking demand is weak, and a lower energy recovery strength is set; when the absolute value of T is in the AB interval, it indicates that the current braking demand is strong, and a higher energy recovery strength is set to convert the kinetic potential energy into electrical energy as much as possible; when the torque of the motor becomes positive again, energy recovery is stopped, and the vehicle maintains a normal driving state.

[0046] The technical solution of the embodiment of the present invention makes the vehicle's estimation of the current state during the downhill process more stable and accurate through the integrated value and convergence variance of the changing parameters at the previous moment; by judging the convergence conditions, the vehicle can determine the target integrated value when the changing parameters tend to be stable, ensuring that the target integrated value is as close as possible to each single changing parameter of the actual integrated value of the changing parameters; using the target integrated value and the real-time collected data of the vehicle to calculate the target torque, it can be ensured that the vehicle's downhill energy recovery is adapted to the current speed, slope and other driving parameters, thereby optimizing the energy recovery efficiency; by controlling the energy recovery force according to the target torque, the energy recovery intensity is adjusted in real time, and a fine control method is implemented, which can effectively recover energy during the vehicle's smooth descent, while avoiding excessive deceleration or insufficient deceleration, thereby improving driving comfort and safety.

[0047] Figure 2 This is a flow chart of a vehicle downhill energy recovery method provided by an embodiment of the present invention. Based on the above embodiments, the embodiment of the present invention optimizes and improves the vehicle downhill energy recovery operation.

[0048] Optionally, "when it is determined that the convergence condition is met based on the change parameter integration value and the convergence variance at the current moment, the change parameter integration value at the current moment is determined as the target integration value" is refined to "calculate the estimated acceleration based on the change parameter integration value and the observation coefficient parameter value at the current moment; calculate the current error between the estimated acceleration and the longitudinal acceleration, and update the cumulative error; calculate the forgetting coefficient at the current moment based on the change parameter integration value and the observation coefficient parameter value at the current moment; when it is determined that the cumulative error and the forgetting coefficient at the current moment meet the convergence condition, determine the change parameter integration value at the current moment as the target integration value" to improve the vehicle's downhill energy recovery operation.

[0049] It should be noted that for parts not described in detail in the embodiments of the present invention, reference may be made to the descriptions of other embodiments.

[0050] See also Figure 2 The vehicle downhill energy recovery method shown includes:

[0051] S201. When determining that the vehicle is traveling steadily downhill, calculate the integrated value and convergence variance of the changing parameters at the current moment based on the integrated value and convergence variance of the changing parameters obtained at the previous moment and the real-time collected data of the vehicle at the current moment; the real-time collected data of the vehicle includes longitudinal acceleration and observation coefficient parameter values.

[0052] Longitudinal acceleration refers to the acceleration experienced by a vehicle in the direction of travel. It represents the rate of change of the vehicle's velocity in that direction. Longitudinal acceleration reflects the vehicle's power output and is a core variable in vehicle dynamics models.

[0053] The observation coefficient parameter value may refer to a set of parameter values ​​composed of real-time vehicle data. The observation coefficient parameter value may include motor torque, gear ratio, main reduction ratio, actual vehicle speed, and 1. The observation coefficient parameter value and the integrated value of the change parameter at a certain moment are combined to obtain the estimated vehicle acceleration at that moment. For example, the observation coefficient parameter value may refer to the measurement matrix [Ti g i0 v1 2 v1 1], where T represents the motor torque, i g represents the gear ratio of the transmission, i0 represents the main reduction ratio, and v1 represents the actual speed of the vehicle. The measurement matrix can associate the dynamic parameters that cannot be directly obtained with the observation values ​​obtained by the sensor. For example, the measurement matrix can associate the integrated value of the changing parameter with the longitudinal acceleration to obtain the target integrated value. When using the recursive least squares method for state estimation, the measurement matrix can map the state vector of the system to the observation space, so that the estimated value can be compared with the actual measured data. By comparing the estimated observation value with the actual observation data, the state estimate is updated.

[0054] S202. Calculate the estimated acceleration based on the integrated value of the change parameter and the observation coefficient parameter value at the current moment.

[0055] The estimated acceleration may be an acceleration estimated based on the integrated value of the variable parameter and the observed coefficient parameter value. The estimated acceleration is used to compare with the true acceleration to obtain the error between the estimated acceleration and the true acceleration.

[0056] S203: Calculate the current error between the estimated acceleration and the longitudinal acceleration, and update the accumulated error.

[0057] Updating the accumulated error may refer to updating and accumulating the error between the estimated acceleration and the longitudinal acceleration. The updated accumulated error is used to determine whether the target integrated value is the optimal parameter in the vehicle longitudinal dynamics model.

[0058] S204. Calculate the forgetting coefficient at the current moment according to the integrated value of the change parameter and the observation coefficient parameter value at the current moment.

[0059] The forgetting coefficient is a parameter used to control the update rate of the recursive least squares method parameters. The closer the forgetting coefficient is to 1, the less influence the updated data has on the estimated parameters. The forgetting coefficient ensures that the influence of updated data on the estimated parameters gradually decreases over time before the convergence condition is met, achieving smooth adjustment.

[0060] S205 . When it is determined that the cumulative error and the forgetting coefficient at the current moment meet the convergence condition, the integrated value of the change parameter at the current moment is determined as the target integrated value.

[0061] S206 : Calculate the target torque based on the target integrated value and the current real-time collected vehicle data.

[0062] S207: Control the energy recovery force according to the target torque.

[0063] It can be seen that in this embodiment, by calculating the current error between the estimated acceleration and the longitudinal acceleration and updating the cumulative error, the error accumulation can be continuously corrected, effectively avoiding the long-term accumulation of errors, and helping to more accurately estimate the integrated value of the changing parameter under various environments and loads; by setting the forgetting coefficient at the current moment, the integrated value of the changing parameter is determined as the target integrated value only when the cumulative error and the forgetting coefficient reach the convergence condition, which reduces the risk of continuous error accumulation and ensures the convergence stability when processing non-steady-state data; the forgetting coefficient can accelerate the convergence response to unstable data and improve the real-time performance of estimating the integrated value of the changing parameter.

[0064] In some embodiments, when it is determined that the cumulative error and the forgetting coefficient at the current moment meet the convergence condition, determining the integrated value of the change parameter at the current moment as the target integrated value includes:

[0065] When the forgetting coefficient at the current moment is greater than the preset coefficient threshold and the cumulative error is less than the preset error threshold, it is determined that the cumulative error and the forgetting coefficient at the current moment meet the convergence condition, and the integrated value of the change parameter at the current moment is determined as the target integrated value.

[0066] The preset coefficient threshold may refer to a forgetting coefficient threshold set in advance, which is used to determine a reference value of the forgetting coefficient at the current moment and serves as one of the criteria for determining whether the current integrated value of the changing parameter has reached convergence.

[0067] The preset error threshold may refer to a cumulative error threshold set in advance, which is used to determine a reference value of the current cumulative error and is used as one of the conditions for determining whether the current integrated value of the cumulative change parameter has reached convergence.

[0068] In a specific example, the integrated value of the changing parameter within a period of time before the integrated value of the changing parameter reaches convergence can be obtained, and the estimated acceleration within this period of time is calculated based on the integrated value of the changing parameter and the observation coefficient parameter value within this period of time, and the error between the estimated acceleration and the actual acceleration within this period of time is calculated, these errors are stored in a storage array, and the error average of the stored data is calculated. When the error average is less than the preset error threshold and the forgetting coefficient is greater than the preset coefficient threshold, it can be determined that the integrated value of the changing parameter at this moment is the optimal parameter of the longitudinal dynamics model of the whole vehicle, that is, the optimal target integration value is obtained.

[0069] It can be seen that in this embodiment, whether the convergence condition is met is determined by the preset coefficient threshold and the preset error threshold. The target integration value at the current moment is determined as the target integration value only when the error is controllable, that is, the average error value is lower than the preset error threshold, and the forgetting coefficient is high, thereby obtaining a more appropriate target integration value.

[0070] In some embodiments, calculating the integrated value and convergence variance of the change parameter at the current moment based on the acquired integrated value and convergence variance of the change parameter at the previous moment and the real-time vehicle data collected at the current moment includes:

[0071] Based on the longitudinal dynamics equation of the vehicle, the integrated value and convergence variance of the change parameters at the previous moment are calculated according to the real-time vehicle data collected at the current moment;

[0072] Among them, the longitudinal dynamics equation of the whole vehicle includes the longitudinal acceleration equal to the product of the real-time collected parameter value and the integrated value of the changing parameter; the real-time status data of the vehicle includes: longitudinal acceleration, torque, gear ratio of the transmission, main reduction ratio and actual vehicle speed; the set of changing parameters includes: transmission efficiency, wheel radius, drag coefficient, air density, frontal area, vehicle environment relative speed, wind speed and rolling resistance coefficient.

[0073] The following formula can be constructed based on the vehicle acceleration equation:

[0074] F 驱动 / 制动 -F 风阻 -F 滚阻 -F 重力 =ma

[0075] Where m represents the vehicle mass, which is a parameter that cannot be obtained by sensors. Since the braking force generated by the vehicle braking system cannot be accurately obtained and has little impact on the present invention, the braking force generated by the vehicle braking system is ignored.

[0076] The driving equation can be expressed as follows:

[0077]

[0078] Where, F 驱动 represents the driving force of the vehicle, T represents the motor torque, η represents the transmission efficiency, i g represents the gear ratio of the transmission, i0 represents the final reduction ratio, and r represents the tire radius. Transmission efficiency and tire radius are parameters that cannot be obtained through sensors.

[0079] The wind resistance equation can be expressed by the following formula:

[0080]

[0081] Where, F 风阻 Indicates the air resistance during vehicle movement, C d The drag coefficient, ρ represents air density, A represents frontal area, v represents vehicle relative speed, v1 represents actual vehicle speed, and v0 represents ambient wind speed. The drag coefficient, air density, frontal area, vehicle relative speed, and ambient wind speed are parameters that cannot be obtained through sensors.

[0082] The rolling resistance equation can be expressed by the following formula:

[0083] F 滚阻 =mgμcosα=mg(b+kv1)cosα

[0084] Where μ represents the rolling resistance coefficient, which can be further decomposed into b + kv1, where k represents the speed-related coefficient and b represents the constant term. The rolling resistance coefficient is a parameter that cannot be obtained through sensors.

[0085] Among them, the gravity equation can be expressed by the following formula:

[0086] F 重力 =mgsinα

[0087] The ramp acceleration equation is expressed as follows:

[0088] a sen =a+gsinα

[0089] Where a sen It represents the vehicle ramp acceleration measured by the sensor, a represents the vehicle acceleration generated by the vehicle power system, g represents gravity, and α represents the inclination angle of the ramp. When the vehicle is driving on a slope, the slope will additionally impose an acceleration component along the ramp direction.

[0090] The longitudinal dynamics equation of the whole vehicle is constructed by combining the vehicle acceleration equation, driving equation, wind resistance equation, rolling resistance equation, gravity equation and slope acceleration equation.

[0091] The longitudinal dynamics equation of the vehicle can be expressed by the following formula:

[0092]

[0093] Where a sen represents longitudinal acceleration, T represents motor torque, η represents transmission efficiency, i g represents the gear ratio of the transmission, i0 represents the main reduction ratio, r represents the wheel radius, C d represents the drag coefficient, ρ represents the air density, A represents the frontal area, v1 represents the relative speed of the vehicle environment, v0 represents the wind speed, and b+kv1 represents the rolling resistance coefficient.

[0094] The longitudinal dynamics equation of the whole vehicle includes the longitudinal acceleration being equal to the product of the real-time collected parameter value and the integrated value of the variable parameter. This can refer to converting the longitudinal dynamics equation of the whole vehicle into a system observation equation. The system observation equation can be expressed by the following formula:

[0095] Z=HX

[0096] Z=a sen

[0097] H=[Ti g i0 v1 2 v1 1]

[0098] x1

[0099]

[0100] x4

[0101] Where Z represents the observation value, which can refer to the slope acceleration and can be obtained by the acceleration sensor; H represents the measurement matrix, and the parameters in the measurement matrix can be obtained by the vehicle's sensors; X represents the integration of parameters that cannot be obtained by the sensor, and X can also refer to the integrated value of the changing parameter.

[0102] In a specific example, the target integrated value can be obtained using the recursive least squares method. The specific implementation formula is as follows:

[0103]

[0104]

[0105]

[0106] In the formula, k represents the number of rounds, represents the integrated value of the changing parameter, γ represents the intermediate variable, z represents the longitudinal acceleration, Represents the measurement matrix, P represents the convergence variance, and the convergence variance is used to determine whether the integrated value of the currently estimated change parameter has completed convergence.

[0107] It can be seen that in this embodiment, by collecting data such as the vehicle's longitudinal acceleration, torque, transmission gear ratio, final reduction ratio and actual speed in real time, the data that can be obtained by the current vehicle can be obtained. By utilizing the integrated value and convergence variance of the changing parameters at the previous moment, historical information can be taken into account when calculating the integrated value of the changing parameters at the current moment, thereby reducing the uncertainty caused by data fluctuations at a single moment, ensuring that the calculation results are more stable, and reducing errors caused by emergencies; the longitudinal dynamics equation of the whole vehicle presents the relationship between the longitudinal acceleration and the real-time parameter value and the integrated value of the changing parameters in the form of a physical model. Through the longitudinal dynamics model of the whole vehicle, the dynamic characteristics of the vehicle can be better understood, so that the calculation results are not only numbers, but also outputs with physical meaning.

[0108] In some embodiments, the target torque is calculated based on the target integrated value and the current real-time vehicle data, including:

[0109] Based on the longitudinal dynamics equation of the vehicle, the target torque is calculated according to the actual vehicle speed, the target integration value and the longitudinal acceleration under the energy recovery state. The longitudinal acceleration under the energy recovery state is zero.

[0110] In the energy recovery state, ensuring that the longitudinal acceleration is zero can ensure a better driving experience for the driver. When the longitudinal acceleration is not zero, the vehicle speed cannot be maintained constant, resulting in a poor driving experience for the driver.

[0111] It can be seen that in this embodiment, through the longitudinal dynamics equation of the whole vehicle, the influence of the vehicle speed on the target torque can be taken into account, so that the calculation process of the target torque conforms to the theoretical model and also meets the driving requirement that the vehicle acceleration is 0 when the vehicle is recovering energy; by setting the acceleration to 0, the calculation of the longitudinal dynamics equation of the whole vehicle is simplified, the calculation complexity is reduced, and the calculation process is made more stable and not easily disturbed by small fluctuations in acceleration, which is conducive to the stable output of the target torque and improves the stability of energy recovery and driving comfort.

[0112] In some embodiments, updating the accumulated error includes:

[0113] Get the accumulated error;

[0114] The current error is added to the accumulated error to update the accumulated error.

[0115] The accumulated error may refer to an iterative accumulated error value, and the accumulated error is updated by adding the current error to the accumulated error.

[0116] It can be seen that in this embodiment, by obtaining the cumulative error value, the current accumulated deviation can be understood before the error is updated, and the error change trend can be identified more accurately; the current error is added to the cumulative error, and the error change is monitored in an accumulated manner. Through this iterative incremental calculation, a basis is provided for subsequent error control.

[0117] In some embodiments, determining that the vehicle is traveling steadily downhill includes:

[0118] When the vehicle communication is normal, the speed sensor is not faulty, the acceleration sensor is not faulty, the actual speed of the vehicle is greater than a preset speed threshold, and the torque is greater than a preset torque threshold, it is determined that the vehicle is traveling steadily downhill.

[0119] It can be seen that in this embodiment, under the premise of normal vehicle communication, the integrity and timeliness of data transmission can be ensured, so that the system can make judgments based on current accurate data; this step lays a reliable data foundation, avoids misjudgments due to communication anomalies, and improves the stability of data processing and the overall reliability of the system.

[0120] In some embodiments, the vehicle is an external cargo vehicle.

[0121] Among them, the vehicle is a vehicle with external cargo, and the vehicle with external cargo may include trucks, vans, box trucks and station wagons. Since the vehicle weight of a fully loaded vehicle and an empty vehicle changes, and the fully loaded vehicle carries cargo, the parameters such as the windward area of ​​the fully loaded vehicle change. Therefore, the embodiment of the present invention is also applicable to vehicles with external cargo.

[0122] It can be seen that in this embodiment, a single parameter in the integrated value of the vehicle variation parameter of the external cargo vehicle under different loads changes. Based on the cargo load of the vehicle, the embodiment of the present invention can provide an accurate longitudinal dynamic model for the vehicle with external cargo.

[0123] In a specific example, the vehicle downhill energy recovery method proposed in an embodiment of the present invention can be applied to scenarios where energy recovery is required during long periods of slow or coasting. When a vehicle is in congestion or driving at low speeds, long periods of slow coasting can create potential energy recovery opportunities. Combining data such as the vehicle's current torque, actual speed, and longitudinal acceleration, the vehicle downhill energy recovery method can automatically switch to an appropriate recovery mode to conserve battery power and improve endurance. In this scenario, energy recovery can be triggered and managed by appropriately setting speed and torque thresholds.

[0124] In a specific example, the vehicle downhill energy recovery method proposed in an embodiment of the present invention can be applied to energy compensation scenarios in off-road or rugged roads. In off-road or complex road conditions, due to frequent acceleration and deceleration caused by road surface changes, excess energy can be recovered in a timely manner when a downhill slope is detected. The timing of energy recovery triggering can be controlled by comparing preset torque and speed thresholds with real-time data. The preset torque can be obtained using the target torque method proposed in an embodiment of the present invention, thereby further optimizing power requirements and energy consumption management for off-road driving.

[0125] By combining the vehicle's longitudinal dynamics equations with real-time parameters such as acceleration, speed, and torque, and through target torque control, energy distribution and vehicle status judgment are optimized, thereby improving energy utilization and enhancing the driving experience.

[0126] Figure 3 This is a schematic diagram of the structure of a vehicle downhill energy recovery device provided by an embodiment of the present invention. The embodiment of the present invention is applicable to the case of vehicle downhill energy recovery. The device can execute the vehicle downhill energy recovery method and can be implemented in the form of hardware and / or software.

[0127] See also Figure 3 The vehicle downhill energy recovery device shown includes: a variable parameter integration value calculation module 301, a target integration value determination module 302, a target torque calculation module 303 and an energy recovery control module 304.

[0128] The variation parameter integration value calculation module 301 is used to calculate the variation parameter integration value and convergence variance at the current moment based on the obtained variation parameter integration value and convergence variance at the previous moment and the real-time vehicle data collected at the current moment when determining that the vehicle is traveling steadily downhill;

[0129] The target integrated value determining module 302 is configured to determine the current integrated value of the changing parameter as the target integrated value when it is determined that the convergence condition is met based on the current integrated value of the changing parameter and the convergence variance;

[0130] The target torque calculation module 303 is used to calculate the target torque based on the target integration value and the current vehicle real-time collected data;

[0131] The energy recovery control module 304 is configured to control the energy recovery strength according to the target torque.

[0132] In some embodiments, the real-time collected data of the vehicle includes longitudinal acceleration and observation coefficient parameter values. When it is determined that the convergence condition is met based on the integrated value of the current changing parameter and the convergence variance, the integrated value of the current changing parameter is determined as the target integrated value. The target integrated value determination module 302 is specifically configured to:

[0133] Calculate the estimated acceleration based on the integrated value of the change parameter at the current moment and the observation coefficient parameter value;

[0134] Calculate the current error between the estimated acceleration and the longitudinal acceleration and update the accumulated error;

[0135] Calculate the forgetting coefficient at the current moment based on the integrated value of the change parameter and the observation coefficient parameter value at the current moment;

[0136] When it is determined that the cumulative error and the forgetting coefficient at the current moment meet the convergence condition, the integrated value of the change parameter at the current moment is determined as the target integrated value.

[0137] In some embodiments, when it is determined that the cumulative error and the forgetting coefficient at the current moment meet the convergence condition, in terms of determining the integrated value of the change parameter at the current moment as the target integrated value, the target integrated value determination module 302 is specifically configured to:

[0138] When the forgetting coefficient at the current moment is greater than the preset coefficient threshold and the cumulative error is less than the preset error threshold, it is determined that the cumulative error and the forgetting coefficient at the current moment meet the convergence condition, and the integrated value of the change parameter at the current moment is determined as the target integrated value.

[0139] In some embodiments, in calculating the current moment's integrated value of the changing parameter and the convergence variance based on the acquired integrated value of the changing parameter and the convergence variance at the previous moment and the collected real-time vehicle data at the current moment, the target integrated value determination module 302 is specifically configured to:

[0140] Based on the longitudinal dynamics equation of the vehicle, the integrated value and convergence variance of the change parameters at the previous moment are calculated according to the real-time vehicle data collected at the current moment;

[0141] Among them, the longitudinal dynamics equation of the whole vehicle includes the longitudinal acceleration equal to the product of the real-time collected parameter value and the integrated value of the changing parameter; the real-time status data of the vehicle includes: longitudinal acceleration, torque, gear ratio of the transmission, main reduction ratio and actual vehicle speed; the set of changing parameters includes: transmission efficiency, wheel radius, drag coefficient, air density, frontal area, vehicle environment relative speed, wind speed and rolling resistance coefficient.

[0142] In some embodiments, in calculating the target torque based on the target integrated value and the current real-time vehicle data, the target integrated value determination module 302 is specifically configured to:

[0143] Based on the longitudinal dynamics equation of the vehicle, the target torque is calculated according to the actual vehicle speed, the target integration value and the longitudinal acceleration under the energy recovery state. The longitudinal acceleration under the energy recovery state is zero.

[0144] In some embodiments, in terms of updating the accumulated error, the target integration value determination module 302 is specifically configured to:

[0145] Get the accumulated error;

[0146] The cumulative error is updated by adding the current error to the cumulative error.

[0147] In some embodiments, in determining whether a vehicle is traveling steadily downhill, the variation parameter integration value calculation module 301 is specifically configured to:

[0148] When the vehicle communication is normal, the speed sensor is not faulty, the acceleration sensor is not faulty, the actual speed of the vehicle is greater than a preset speed threshold, and the torque is greater than a preset torque threshold, it is determined that the vehicle is traveling steadily downhill.

[0149] In some embodiments, the vehicle is an external cargo vehicle.

[0150] The technical solution of the embodiment of the present invention makes the vehicle's estimation of the current state during the downhill process more stable and accurate through the integrated value and convergence variance of the changing parameters at the previous moment; by judging the convergence conditions, the vehicle can determine the target integrated value when the changing parameters tend to be stable, ensuring that the target integrated value is as close as possible to each single changing parameter of the actual integrated value of the changing parameters; using the target integrated value and the real-time collected data of the vehicle to calculate the target torque, it can be ensured that the vehicle's downhill energy recovery is adapted to the current speed, slope and other driving parameters, thereby optimizing the energy recovery efficiency; by controlling the energy recovery force according to the target torque, the energy recovery intensity is adjusted in real time, and a fine control method is implemented, which can effectively recover energy during the vehicle's smooth descent, while avoiding excessive deceleration or insufficient deceleration, thereby improving driving comfort and safety.

[0151] The vehicle downhill energy recovery device provided in the embodiment of the present invention can execute the vehicle downhill energy recovery method provided in any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the vehicle downhill energy recovery method.

[0152] Figure 4 The figure is a schematic structural diagram of a vehicle downhill energy recovery device provided according to an embodiment of the present invention.

[0153] like Figure 4 As shown, the vehicle downhill energy recovery device 400 includes at least one processor 401, and a memory connected to the at least one processor 401 in communication, such as a read-only memory (ROM) 402, a random access memory (RAM) 403, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 401 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 402 or the computer program loaded from the storage unit 408 to the random access memory (RAM) 403. Various programs and data required for the operation of the vehicle downhill energy recovery device 400 can also be stored in the RAM 403. The processor 401, ROM 402 and RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0154] Multiple components in the vehicle downhill energy recovery device 400 are connected to an I / O interface 405, including an input unit 406, such as a keyboard and mouse; an output unit 407, such as various types of displays and speakers; a storage unit 408, such as a magnetic disk and optical disk; and a communication unit 409, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 409 allows the vehicle downhill energy recovery device 400 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0155] Processor 401 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of processor 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processor, controller, microcontroller, etc. Processor 501 executes the various methods and processes described above, such as the vehicle downhill energy recovery method.

[0156] In some embodiments, the vehicle downhill energy recovery method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 408. In some embodiments, part or all of the computer program can be loaded and / or installed on the vehicle downhill energy recovery device 400 via the ROM 402 and / or the communication unit 409. When the computer program is loaded into the RAM 403 and executed by the processor 401, one or more steps of the vehicle downhill energy recovery method described above can be performed. Alternatively, in other embodiments, the processor 401 can be configured to execute the vehicle downhill energy recovery method by any other appropriate means (for example, by means of firmware).

[0157] Various embodiments of the systems and techniques described above can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0158] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0159] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0160] To provide interaction with the user, the systems and techniques described herein can be implemented on an operation detection device, which has: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball), through which the user can provide input to the vehicle downhill energy recovery device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0161] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0162] A computing system may include clients and servers. The clients and servers are generally remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within a cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS (Virtual Private Server) services.

[0163] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0164] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A method for recovering energy when a vehicle is going downhill, characterized in that: The method comprises: When determining that the vehicle is traveling steadily downhill, the integrated value of the change parameter and the convergence variance at the current moment are calculated based on the integrated value of the change parameter and the convergence variance obtained at the previous moment and the real-time data collected by the vehicle at the current moment; When it is determined that the convergence condition is satisfied according to the integrated value of the change parameter at the current moment and the convergence variance, the integrated value of the change parameter at the current moment is determined as the target integrated value; Calculating a target torque based on the target integrated value and the real-time collected data of the vehicle at the current moment; controlling the energy recovery strength according to the target torque; The real-time collected data of the vehicle include longitudinal acceleration and observation coefficient parameter values; The step of determining the integrated value of the change parameter at the current moment as the target integrated value when the convergence condition is determined to be satisfied according to the integrated value of the change parameter at the current moment and the convergence variance includes: Calculating an estimated acceleration based on the integrated value of the change parameter at the current moment and the observation coefficient parameter value; calculating a current error between the estimated acceleration and the longitudinal acceleration, and updating a cumulative error; Calculating the forgetting coefficient at the current moment according to the integrated value of the change parameter at the current moment and the observation coefficient parameter value; When it is determined that the accumulated error and the forgetting coefficient at the current moment satisfy a convergence condition, the integrated value of the change parameter at the current moment is determined as the target integrated value.

2. The method according to claim 1, characterized in that When it is determined that the accumulated error and the forgetting coefficient at the current moment satisfy a convergence condition, determining the integrated value of the change parameter at the current moment as a target integrated value includes: When the forgetting coefficient at the current moment is greater than a preset coefficient threshold and the cumulative error is less than a preset error threshold, it is determined that the cumulative error and the forgetting coefficient at the current moment meet a convergence condition, and the integrated value of the change parameter at the current moment is determined as a target integrated value.

3. The method according to claim 1, characterized in that The step of calculating the integrated value of the change parameter and the convergence variance at the current moment based on the acquired integrated value of the change parameter and the convergence variance at the previous moment and the real-time vehicle data collected at the current moment includes: Based on the longitudinal dynamics equation of the vehicle, the integrated value and convergence variance of the change parameters at the previous moment are calculated according to the real-time vehicle data collected at the current moment; Among them, the longitudinal dynamics equation of the whole vehicle includes that the longitudinal acceleration is equal to the product of the real-time collected parameter value and the integrated value of the variable parameter; the real-time status data of the vehicle includes: longitudinal acceleration, torque, gear ratio of the transmission, main reduction ratio and actual speed of the vehicle; the variable parameter set includes: transmission efficiency, wheel radius, drag coefficient, air density, frontal area, vehicle environment relative speed, wind speed and rolling resistance coefficient.

4. The method according to claim 3, characterized in that The calculating of the target torque according to the target integrated value and the real-time collected data of the vehicle at the current moment includes: The target torque is calculated based on the longitudinal dynamics equation of the entire vehicle according to the actual vehicle speed, the target integrated value and the longitudinal acceleration in the energy recovery state, where the longitudinal acceleration in the energy recovery state is zero.

5. The method according to claim 1, wherein The updating of the accumulated error includes: Get the accumulated error; The accumulated error is updated by adding the current error to the accumulated error.

6. The method according to claim 1, characterized in that The step of determining that the vehicle is traveling smoothly downhill comprises: When the vehicle communication is normal, the speed sensor is not faulty, the acceleration sensor is not faulty, the actual speed of the vehicle is greater than a preset speed threshold, and the torque is greater than a preset torque threshold, it is determined that the vehicle is traveling steadily downhill.

7. The method according to claim 1, characterized in that The vehicle is an external cargo vehicle.

8. A vehicle downhill energy recovery device, characterized in that: The device comprises: A change parameter integration value calculation module is used to calculate the change parameter integration value and convergence variance at the current moment based on the acquired change parameter integration value and convergence variance at the previous moment and the real-time vehicle data collected at the current moment when determining that the vehicle is traveling steadily downhill; a target integrated value determining module, configured to determine the integrated value of the changing parameter at the current moment as the target integrated value when it is determined that the convergence condition is met based on the integrated value of the changing parameter at the current moment and the convergence variance; a target torque calculation module, configured to calculate the target torque based on the target integrated value and the real-time collected vehicle data at the current moment; The energy recovery control module is used to control the energy recovery force according to the target torque.

9. A vehicle downhill energy recovery device, characterized in that: The vehicle downhill energy recovery device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the vehicle downhill energy recovery method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the vehicle downhill energy recovery method according to any one of claims 1 to 7 when executed.

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