Vehicle downhill energy recovery method, device, equipment and medium

Abstract

The invention discloses a vehicle downhill energy recovery method, device and equipment and a medium. The method comprises the steps of calculating a change parameter integration value and a convergence variance at a current moment according to an obtained change parameter integration value and a convergence variance at a previous moment and collected vehicle real-time collection data at the current moment when it is determined that a vehicle stably travels downhill; when it is determined that a convergence condition is met according to the change parameter integration value at the current moment and the convergence variance, determining the change parameter integration value at the current moment as a target integration value; calculating a target torque according to the target integration value and vehicle real-time acquisition data at the current moment; and controlling the energy recovery strength according to the target torque. The embodiment of the 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 vehicle downhill energy recovery method, device, equipment and medium. 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 recovering energy when a vehicle is going downhill.

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

[0007] When determining that the vehicle is driving 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 real-time collected data of the vehicle at the current moment;

[0010] Controls the energy recovery strength according to the 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] The change parameter integration value calculation module is used to calculate the change parameter integration value and convergence variance at the current moment according to the acquired change parameter integration value and convergence variance at the previous moment and the collected real-time vehicle data at the current moment when determining that the vehicle is driving steadily downhill;

[0013] A target integration value determination module is used to determine the current change parameter integration value as the target integration value when it is determined that the convergence condition is met according to the current change parameter integration value and the convergence variance;

[0014] A 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 strength 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 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, wherein 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 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 change parameter at the previous moment; through the judgment of the convergence condition, the vehicle can determine the target integrated value when the change parameter tends to be stable, ensuring that the target integrated value is close to each single change parameter of the real change parameter integrated value; using the target integrated value and the real-time collected data of the vehicle to calculate the target torque, it can ensure 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 intensity according to the target torque, the energy recovery intensity can be adjusted in real time, and a fine control method can be achieved, so that energy can be effectively recovered during the vehicle's stable downhill process, while avoiding excessive deceleration or insufficient deceleration, thereby improving driving comfort and safety.

[0022] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily 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 accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

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

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

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

[0027] Figure 4 It is a structural schematic 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 scheme of the present invention, the technical scheme 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 described embodiments 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 creative work should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first", "second", etc. in the specification 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 data 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 that are 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 solution of the embodiment of the present invention, the acquisition, storage and application of real-time vehicle data collected, etc. are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0031] Figure 1A flowchart of a vehicle downhill energy recovery method provided by an embodiment of the present invention. The embodiment of the present invention is applicable to the case of vehicle downhill energy recovery, and the method can be performed by a vehicle downhill energy recovery device, which can be implemented in the form of 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 according to the integrated value of the change parameter and the convergence variance acquired at the previous moment and the real-time collected data of the vehicle at the current moment.

[0034] Among them, the integrated value of the changing parameter can refer to the estimated value of the integrated value of the changing parameter that cannot be obtained by the sensor. The estimated value of the integrated value can be obtained by integrating and calculating the relevant changing parameters of the longitudinal dynamics of the vehicle. For example, the integrated value of the changing parameter can be an estimated value of the comprehensive value obtained according to the changes in the load weight, volume and shape. There are multiple changing parameters, and the changing parameters can include transmission efficiency, tire radius, vehicle mass, drag coefficient, air density, windward area, vehicle relative speed, ambient wind speed and rolling resistance coefficient. Through the collected data, it is impossible to accurately determine the precise value of a single changing parameter in these changing parameters, and only the estimated value of the relationship of the combination of these changing parameters can be determined, and the estimated value of the relationship of the combination is the integrated value of the changing parameter. Since the value of a single changing parameter in these changing parameters is affected by many factors, for example, the tire is slightly deformed due to load, temperature and speed during driving, resulting in an unfixed actual radius of the tire, the integrated value of the changing parameter that cannot be obtained can be estimated based on the parameter value that can be obtained, and an estimated value approximating the actual parameter can be obtained, and the exact value cannot be obtained. Among them, the parameter values ​​that can be obtained may include motor torque, gear ratio of the transmission, main reduction ratio, actual vehicle speed and longitudinal acceleration and other parameter values.

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

[0036] S102: 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.

[0037] Among them, the convergence condition may refer to the 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 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, the integrated value of the changing parameters at the current moment is determined to be the target integrated value. 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, the integrated value of the changing parameters at the current moment is determined to be the target integrated value, and the target integrated value is used as the optimal parameter of the longitudinal dynamics model of the whole vehicle.

[0038] The target integrated value may refer to the integrated value of the change parameter when the convergence condition is met. When the convergence condition is met, the integrated value of the change parameter under the condition is determined as the target integrated value, and the target integrated value may be identified as the vehicle dynamics parameter that best represents the current vehicle driving state. The target integrated value is the basic value for calculating the target torque, providing an estimate that is closest to the actual vehicle dynamics parameter, making the subsequent calculation process more accurate.

[0039] S103, calculating the target torque according to the target integrated value and the real-time collected data of the vehicle at the current moment.

[0040] The target torque may refer to the motor braking torque required when the vehicle acceleration is kept at zero. The target torque is based on the target integration value and the real-time data collected by the vehicle. The target torque can be calculated by the vehicle longitudinal dynamics equation. The value of the target torque meter can be used to determine whether to perform downhill energy recovery. When the target torque is positive, energy recovery is stopped. When the target torque is negative, energy recovery is enabled, so that stable vehicle braking force can be achieved.

[0041] In a specific example, ideally, when the vehicle acceleration is zero, the vehicle speed remains unchanged, which can avoid a poor driving experience caused by repeated changes in the 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: Controlling energy recovery strength according to target torque.

[0045] Among them, the energy recovery strength may refer to the strength of controlling the energy recovery of the vehicle 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, the vehicle can be prevented from being unstable due to excessive energy recovery strength, and a stable speed and state can be maintained on the downhill, which can improve the driving comfort and energy recovery efficiency. Exemplarily, when the target torque is negative, the vehicle is performing 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 means 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 means 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 change parameter at the previous moment; through the judgment of the convergence condition, the vehicle can determine the target integrated value when the change parameter tends to be stable, and ensure that the target integrated value is as close as possible to each single change parameter of the real change parameter integrated value; the target integrated value and the real-time collected data of the vehicle are used to calculate the target torque, which can ensure 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 intensity according to the target torque, the energy recovery intensity can be adjusted in real time, and a fine control method can be achieved, so that energy can be effectively recovered during the vehicle's stable downhill process, while avoiding excessive deceleration or insufficient deceleration, thereby improving driving comfort and safety.

[0047] Figure 2 The present invention provides a flow chart of a vehicle downhill energy recovery method. The present invention optimizes and improves the vehicle downhill energy recovery operation based on the above embodiments.

[0048] Optionally, "when it is determined that the convergence condition is met based on the integrated value of the changing parameters at the current moment and the convergence variance, the integrated value of the changing parameters at the current moment is determined as the target integrated value" is refined into "calculating the estimated acceleration based on the integrated value of the changing parameters at the current moment and the observed coefficient parameter value; calculating the current error between the estimated acceleration and the longitudinal acceleration, and updating the cumulative error; calculating the forgetting coefficient at the current moment based on the integrated value of the changing parameters at the current moment and the observed coefficient parameter value; 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 changing parameters at the current moment as the target integrated value" to improve the vehicle's downhill energy recovery operation.

[0049] It should be noted that for the 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 driving 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 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] Among them, longitudinal acceleration can refer to the acceleration of the vehicle in the direction of travel. Longitudinal acceleration represents the rate of change of the vehicle's speed in this direction. Longitudinal acceleration reflects the power output of the vehicle, and longitudinal acceleration is also the core variable in the vehicle dynamics model.

[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 gearbox, 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 can be 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 refer to the acceleration estimated according to the integrated value of the variation parameter and the observation coefficient parameter value. The estimated acceleration is used to compare with the real acceleration to obtain the error between the estimated acceleration and the real acceleration.

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

[0057] Wherein, updating the accumulated error may refer to updating and accumulating the error between the estimated acceleration and the longitudinal acceleration, and updating the accumulated error is used to determine whether the target integration value is the best parameter in the longitudinal dynamics model of the whole vehicle.

[0058] S204. Calculate 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.

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

[0060] S205. When it is determined that the accumulated 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 , calculating the target torque according to the target integrated value and the real-time collected data of the vehicle at the current moment.

[0062] S207: Control the energy recovery strength 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 accumulated error, the error accumulation can be continuously corrected, which effectively avoids the long-term accumulation of errors and helps to more accurately estimate the integrated value of the changing parameters under various environments and loads; by setting the forgetting coefficient at the current moment, the integrated value of the changing parameters is determined as the target integrated value only when the accumulated error and the forgetting coefficient reach the convergence condition, which reduces the risk of continuous accumulation of errors and ensures the convergence stability when processing non-steady-state data; the forgetting coefficient can speed up the convergence response to unstable data and improve the real-time performance of estimating the integrated value of the changing parameters.

[0064] In some embodiments, when it is determined that the accumulated 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. The preset coefficient threshold is used to determine the reference value of the forgetting coefficient at the current moment, as one of the criteria for determining whether the current change parameter integration value reaches convergence.

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

[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, and 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 a 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, the preset coefficient threshold and the preset error threshold are used to determine whether the convergence condition is met. The target integration value at the current moment is determined as the target integration value only when the error is controllable, that is, the error average is lower than the preset error threshold, and the forgetting coefficient is high, so as to obtain a more suitable target integration value.

[0070] In some embodiments, the integrated value and convergence variance of the change parameter at the previous moment are calculated 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, including:

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

[0072] Among them, the longitudinal dynamics equation of the whole vehicle includes the longitudinal acceleration which is 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 include: longitudinal acceleration, torque, gear ratio of the transmission, main reduction ratio and actual vehicle speed; the set of changing parameters include: 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] In the formula, m represents the mass of the vehicle, wherein the mass of the vehicle is a parameter that cannot be obtained by the sensor. Since the braking force generated by the vehicle braking system cannot be accurately obtained and has little effect on the present invention, the braking force generated by the vehicle braking system is ignored.

[0076] The driving equation can be expressed by the following formula:

[0077]

[0078] In the formula, 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 gearbox, i0 represents the main reduction ratio, and r represents the tire radius. Among them, the 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] In the formula, F 风阻 Indicates the air resistance of the vehicle during driving, C d represents the drag coefficient, ρ represents the air density, A represents the frontal area, v represents the relative speed of the vehicle, v1 represents the actual speed of the vehicle, and v0 represents the ambient wind speed. Among them, the drag coefficient, air density, frontal area, relative speed of the vehicle and ambient wind speed are parameters that cannot be obtained by sensors.

[0082] Among them, the rolling resistance equation can be expressed by the following formula:

[0083] F 滚阻 =mgμcosα=mg(b+kv1)cosα

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

[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 by the following formula:

[0088] a sen =a+gsinα

[0089] In the formula, 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 apply 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 ramp acceleration equation.

[0091] Among them, the longitudinal dynamics equation of the whole vehicle can be expressed by the following formula:

[0092]

[0093] In the formula, a sen represents longitudinal acceleration, T represents motor torque, η represents transmission efficiency, i g represents the gear ratio of the gearbox, 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] Among them, the longitudinal dynamics equation of the whole vehicle includes that the longitudinal acceleration is equal to the product between the real-time acquisition parameter value and the integrated value of the change parameter, which 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] Wherein, Z represents the observed value, which may refer to the ramp acceleration and can be obtained through the acceleration sensor; H represents the measurement matrix, and the parameters in the measurement matrix can be obtained through the vehicle's sensor; X represents the integration of parameters that cannot be obtained through the sensor, and X may also refer to the integrated value of the variable 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 variable 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 current estimated change parameter has completed convergence.

[0107] It can be seen that in this embodiment, by collecting data such as the longitudinal acceleration, torque, gear ratio, main reduction ratio and actual speed of the vehicle in real time, the data that the current vehicle can obtain can be obtained. By using the integrated value of the changing parameters and the convergence variance at the previous moment, when calculating the integrated value of the changing parameters at the current moment, historical information can be taken into account to reduce the uncertainty caused by data fluctuations at a single moment, ensure that the calculation results are more stable, and reduce 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 real-time collected data of the vehicle at the current moment, including:

[0109] Based on the longitudinal dynamics equation of the whole 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 good 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 is consistent with the theoretical model, and also meets the driving requirements of the vehicle that the vehicle acceleration is 0 when the vehicle recovers 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 affected 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 driving 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 misjudgment 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, parameters such as the windward area of ​​the fully loaded vehicle change. Therefore, the embodiments of the present invention are 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 of the vehicle, the embodiment of the present invention can provide an accurate longitudinal dynamic model for the external cargo vehicle.

[0123] In a specific example, the vehicle downhill energy recovery method proposed in an embodiment of the present invention can be applied to the scenario of long-term slow driving or coasting energy recovery. When the vehicle is in congestion or driving at a low speed, long-term slow coasting can bring potential energy recovery opportunities. Combined with data such as the vehicle's current torque, actual speed and longitudinal acceleration, the vehicle downhill energy recovery method can automatically switch to a suitable recovery mode to save battery power and improve battery life. In this scenario, the triggering and management of energy recovery can be achieved by appropriately setting speed and torque thresholds.

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

[0125] Through the longitudinal dynamics equation of the whole vehicle, combined with real-time parameters such as actual acceleration, speed, torque, and target torque control, energy distribution and vehicle status judgment are optimized, thereby improving energy utilization and enhancing driving experience.

[0126] Figure 3 The present invention provides a schematic diagram of a downhill vehicle energy recovery device. The present invention is applicable to downhill vehicle energy recovery. The device can execute a downhill vehicle energy recovery method. The device 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, wherein:

[0128] The change parameter integration value calculation module 301 is used to calculate the change parameter integration value and convergence variance at the current moment according to 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 driving steadily downhill;

[0129] The target integrated value determination module 302 is used 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 according to 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 according to the target integration value and the real-time collected data of the vehicle at the current moment;

[0131] The energy recovery control module 304 is used 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 according to the integrated value of the changed parameter at the current moment and the convergence variance, the integrated value of the changed parameter at the current moment is determined as the target integrated value. The target integrated value determination module 302 is specifically used to:

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

[0136] When it is determined that the accumulated 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, the integrated value of the change parameter at the current moment is determined as the target integrated value. The target integrated value determination module 302 is specifically used 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 terms of calculating the integrated value of the change parameter and the convergence variance at the current moment according to the acquired integrated value of the change parameter at the previous moment and the convergence variance and the collected real-time vehicle data at the current moment, the target integrated value determination module 302 is specifically used to:

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

[0141] Among them, the longitudinal dynamics equation of the whole vehicle includes the longitudinal acceleration which is 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 include: longitudinal acceleration, torque, gear ratio of the transmission, main reduction ratio and actual vehicle speed; the set of changing parameters include: 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 terms of calculating the target torque according to the target integrated value and the real-time vehicle data collected at the current moment, the target integrated value determination module 302 is specifically used to:

[0143] Based on the longitudinal dynamics equation of the whole 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 current error is added to the accumulated error to update the accumulated error.

[0147] In some embodiments, in determining whether the vehicle is driving downhill smoothly, the variation parameter integration value calculation module 301 is specifically used 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 driving 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 change parameter at the previous moment; through the judgment of the convergence condition, the vehicle can determine the target integrated value when the change parameter tends to be stable, and ensure that the target integrated value is as close as possible to each single change parameter of the real change parameter integrated value; the target integrated value and the real-time collected data of the vehicle are used to calculate the target torque, which can ensure 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 intensity according to the target torque, the energy recovery intensity can be adjusted in real time, and a fine control method can be achieved, so that energy can be effectively recovered during the vehicle's stable downhill process, 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 It is a structural schematic 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. In RAM403, various programs and data required for the operation of the vehicle downhill energy recovery device 400 can also be stored. The processor 401, ROM402 and RAM403 are connected to each other through 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 the I / O interface 405, including: an input unit 406, such as a keyboard, a mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a disk, an optical disk, etc.; 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 through a computer network such as the Internet and / or various telecommunication networks.

[0155] Processor 401 may be a variety of general and / or special processing components 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 processors, controllers, microcontrollers, etc. Processor 501 performs the various methods and processes described above, such as a 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 ROM402 and / or communication unit 409. When the computer program is loaded into RAM403 and executed by processor 401, one or more steps of the vehicle downhill energy recovery method described above can be performed. Alternatively, in other embodiments, processor 401 can be configured to execute the vehicle downhill energy recovery method in any other appropriate manner (for example, by means of firmware).

[0157] Various implementations of the systems and techniques described above herein 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), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including 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, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

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

[0160] In order 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 a pointing device (e.g., a mouse or a 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 the 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 may be implemented in a computing system that includes backend 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 frontend components (e.g., a user computer with a graphical user interface or a 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 backend components, middleware components, or frontend components. The components of the system may 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 a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS (Virtual Private Server) services.

[0163] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0164] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A vehicle downhill energy recovery method, characterized in that: The method comprises: When determining that the vehicle is driving 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 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; Calculating a target torque according to the target integrated value and the real-time collected data of the vehicle at the current moment; The energy recovery strength is controlled according to the target torque.

2. The method according to claim 1, characterized in that 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 satisfied according to the integrated value of the change parameter at the current moment and the convergence variance includes: Calculating an estimated acceleration according to the integrated value of the variation 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.

3. The method according to claim 2, 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 the target integrated value includes: 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.

4. The method according to claim 2, 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 collected real-time vehicle data at the current moment includes: Based on the longitudinal dynamics equation of the whole vehicle, the integrated value and convergence variance of the changed parameters at the previous moment are calculated according to the acquired real-time data of the vehicle 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 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.

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

6. The method according to claim 2, characterized in that 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.

7. The method according to claim 1, characterized in that The step of determining that the vehicle is traveling steadily 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 driving steadily downhill.

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

9. A vehicle downhill energy recovery device, characterized in that: The device comprises: The change parameter integration value calculation module is used to calculate the change parameter integration value and convergence variance at the current moment according to the acquired change parameter integration value and convergence variance at the previous moment and the collected real-time vehicle data at the current moment when determining that the vehicle is driving steadily downhill; 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 according to the integrated value of the changing parameter at the current moment and the convergence variance; A target torque calculation module, used to calculate the target torque according to the target integrated value and the real-time collected data of the vehicle at the current moment; The energy recovery control module is used to control the energy recovery strength according to the target torque.

10. 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 8.

11. 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 8 when executed.

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