Vehicle mass determination method and device, electronic equipment and storage medium

Abstract

The invention provides a vehicle quality determination method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a preset first mass of a vehicle, and performing parameter detection on the vehicle at a first moment in a vehicle driving process to obtain a first driving parameter of the vehicle at the first moment; based on the first driving parameter, updating the first mass to obtain a second mass of the vehicle; parameter detection is conducted on the vehicle at multiple second moments in the vehicle driving process, second driving parameters of the vehicle at each second moment are obtained, and the second moments are later than the first moment; and iteratively updating the second quality based on the second driving parameter at the second moment to obtain the target quality of the vehicle. According to the invention, the accuracy of the quality of the vehicle can be effectively improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computers, and in particular to a vehicle mass determination method and device, an electronic device, and a storage medium. BACKGROUND

[0002] With the increasing requirements of people on automobiles, automobile technology is also constantly improving. Corresponding automobile-related functions also need to be constantly updated and optimized. Accurate vehicle mass can greatly affect the vehicle's handling and braking performance. The greater the mass, the greater the inertia, the longer the braking distance, and the slower the steering response. Mass estimation can guide the design of the braking system (such as brake pad size, brake pump pressure) and the suspension system (such as spring stiffness) to ensure handling safety. At the same time, the mass of the automobile can also affect the power matching and oil / electricity consumption control of the vehicle. If the mass estimation deviates greatly, it may lead to insufficient engine / motor power (acceleration is weak) or excessive power (waste of energy). Accurate mass estimation can help optimize power system parameters (such as transmission gear ratio, motor torque) and reduce energy consumption.

[0003] In related technologies, the mass of the vehicle is usually determined by a one-time determination of the vehicle using a dynamic method. Since there are unstable data in the single determination process, the determined mass is less accurate. SUMMARY

[0004] The embodiments of the present application provide a vehicle mass determination method, device, electronic device, computer-readable storage medium, and computer program product, which can effectively improve the accuracy of the mass of the vehicle.

[0005] The technical solutions of the embodiments of the present application are as follows: The embodiments of the present application provide a vehicle mass determination method, comprising: obtaining a first mass of the vehicle, and performing parameter detection on the vehicle at a first time during the driving of the vehicle to obtain a first driving parameter of the vehicle at the first time; updating the first mass based on the first driving parameter to obtain a second mass of the vehicle; performing parameter detection on the vehicle at a plurality of second times during the driving of the vehicle to obtain a second driving parameter of the vehicle at each second time, the second time being later than the first time; iteratively updating the second mass based on the second driving parameter at the second time to obtain a target mass of the vehicle.

[0006] The embodiments of the present application provide a vehicle mass determination device, comprising: The first detection module is configured to obtain a first mass of the vehicle, and perform parameter detection on the vehicle at a first time during driving of the vehicle to obtain a first driving parameter of the vehicle at the first time. The first updating module is configured to update the first mass based on the first driving parameter to obtain a second mass of the vehicle. The second detection module is configured to perform parameter detection on the vehicle at a plurality of second times during driving of the vehicle to obtain a second driving parameter of the vehicle at each of the second times, the second times being later than the first time. The second updating module is configured to iteratively update the second mass based on the second driving parameter at the second time to obtain a target mass of the vehicle.

[0007] An electronic device is provided in an embodiment of the present application, and the electronic device includes: A memory is configured to store computer executable instructions or computer programs. A processor is configured to execute the computer executable instructions or computer programs stored in the memory to implement the mass determination method of the vehicle provided in the embodiments of the present application.

[0008] A computer readable storage medium is provided in an embodiment of the present application, and the computer readable storage medium stores computer executable instructions or computer programs, and is configured to cause a processor to execute the mass determination method of the vehicle provided in the embodiments of the present application.

[0009] An embodiment of the present application provides a computer program product, which includes a computer program or computer executable instructions stored in a computer readable storage medium. A processor of an electronic device reads the computer executable instructions or computer programs from the computer readable storage medium, and the processor executes the computer executable instructions or computer programs, so that the electronic device executes the mass determination method of the vehicle provided in the embodiments of the present application.

[0010] The embodiments of the present application have the following beneficial effects: By acquiring the preset initial mass of the vehicle, the initial mass is updated for the first time by using the real-time driving parameters at the first time to obtain the intermediate mass, which avoids the problem of large deviation from the actual mass of the vehicle caused by relying only on the preset initial mass. Then, the intermediate mass is iteratively updated by using the real-time driving parameters collected at multiple subsequent driving times later than the first time to obtain the target mass. The real-time driving parameters at multiple subsequent times can comprehensively capture the dynamic changes of the mass of the vehicle during driving, effectively covering the mass fluctuation characteristics under different driving conditions, and the iterative updating process can gradually filter the errors that may exist in single parameter detection and the deviation caused by single updating, so that the mass data continuously converges to the actual mass state of the vehicle in multiple rounds of calibration. The progressive mass updating logic from initial calibration to multiple rounds of iterative optimization can correct the deviation between the mass data and the actual mass layer by layer, significantly reduce the influence of various interference factors on mass evaluation, and effectively improve the accuracy of the mass of the vehicle. BRIEF DESCRIPTION OF DRAWINGS

[0011] Figure 1 is an architecture schematic diagram of a mass determination system of a vehicle provided by an embodiment of the present application; Figure 2 is a structure schematic diagram of an electronic device for determining the mass of a vehicle provided by an embodiment of the present application; Figure 3 is a flow schematic diagram of a mass determination method of a vehicle provided by an embodiment of the present application Figure 1 ; Figure 4 is a flow schematic diagram of a mass determination method of a vehicle provided by an embodiment of the present application Figure 2 ; Figure 5 is a flow schematic diagram of a mass determination method of a vehicle provided by an embodiment of the present application Figure 3 . DETAILED DESCRIPTION

[0012] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application will be described in further detail below with reference to the drawings, and the described embodiments should not be regarded as limiting the present application. All other embodiments obtained by those of ordinary skill in the art without making creative efforts fall within the scope of protection of the present application.

[0013] In the following description, "some embodiments" are described, which describe a subset of all possible embodiments, but it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict.

[0014] In the following description, the terms "first", "second", "third", etc. are merely used to distinguish similar objects, and do not represent a specific order or sequence for the objects. Understandably, the "first", "second", "third" can be interchanged in a specific order or sequence as allowed, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein.

[0015] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in this application is for the purpose of describing the embodiments of this application only, and is not intended to limit this application.

[0016] Referring to Figure 1 , Figure 1 is an architecture diagram of a vehicle mass determination system 100 provided by an embodiment of the application. A terminal (exemplarily shown as terminal 400) is connected to a server 200 through a network 300. The network 300 can be a wide area network or a local area network, or a combination of the two.

[0017] The terminal 400 is used by a user to use a client 410, and a target mass is displayed on a graphical interface 410-1 (exemplarily shown as graphical interface 410-1). The terminal 400 and the server 200 are connected to each other through a wired or wireless network.

[0018] In some embodiments, the server 200 can be a standalone physical server, or a server cluster composed of multiple physical servers, or a business system, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms, etc. The terminal 400 can be a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart television, a smart watch, a vehicle terminal, etc., but is not limited thereto. The electronic device provided by an embodiment of the application can be implemented as a terminal or a server. The terminal and the server can be directly or indirectly connected through wired or wireless communication, which is not limited in the embodiments of the application.

[0019] Referring to Figure 2 , Figure 2 is a structural diagram of an electronic device 500 for determining the mass of a vehicle provided by an embodiment of the application, wherein Figure 2 The electronic device 500 shown can be the server 200 or the terminal 400 in Figure 1 , Figure 2The electronic device 500 shown includes at least one processor 430, a memory 450, at least one network interface 420. The various components in the electronic device 500 are coupled together by a bus system 440. It can be understood that the bus system 440 is used to realize the connection communication between the components. In addition to including a data bus, the bus system 440 also includes a power supply bus, a control bus, and a status signal bus. However, for the sake of clarity, all the buses are marked as the bus system 440 in the Figure 2

[0020] The processor 430 can be an integrated circuit chip having a processing capability of a signal, such as a general-purpose processor, a digital signal processor (DSP), or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, etc., wherein the general-purpose processor can be a microprocessor or any conventional processor.

[0021] The memory 450 can be removable, non-removable, or a combination thereof. Exemplary hardware devices include solid-state memory, hard disk drive, optical disk drive, etc. The memory 450 can optionally include one or more storage devices that are physically located away from the processor 430. The memory 450 includes volatile memory or non-volatile memory, and can also include both volatile and non-volatile memory.

[0022] In some embodiments, the memory 450 is capable of storing data to support various operations, examples of which include programs, modules, and data structures or subsets or supersets thereof, which are exemplarily illustrated below.

[0023] The operating system 451 includes system programs for processing various basic system services and performing hardware-related tasks, such as a framework layer, a core library layer, a driver layer, etc., for implementing various basic services and processing hardware-based tasks. The network communication module 452 is used to reach other electronic devices via one or more (wired or wireless) network interfaces 420, and exemplary network interfaces 420 include Bluetooth, Wireless Fidelity (WiFi), and Universal Serial Bus (USB), etc.

[0024] In some embodiments, the mass determination device of the vehicle provided by the embodiments of the present application can be realized in a software manner, Figure 2 ​A vehicle quality determination device 455 stored in memory 450 is shown. This device can be software in the form of programs and plug-ins, and includes the following software modules: a first detection module 4551, a first update module 4552, a second detection module 4553, and a second update module 4554. These modules are logically connected and can therefore be arbitrarily combined or further separated according to their implemented functions. The functions of each module will be described below.

[0025] The method for determining vehicle quality provided in this application will be described in conjunction with exemplary applications and implementations of the server or terminal provided in the embodiments of this application.

[0026] See Figure 3 , Figure 3 This is a flowchart illustrating the vehicle mass determination method provided in the embodiments of this application. Figure 1 , will combine Figure 3 Steps 101 to 104 are described below. The vehicle quality determination method provided in this application embodiment can be implemented by the server or the terminal alone, or by the server and the terminal working together. The following description will take the implementation by the server alone as an example.

[0027] In step 101, a preset first mass of the vehicle is obtained, and at a first moment during the vehicle's operation, parameters of the vehicle are detected to obtain the first driving parameters of the vehicle at the first moment.

[0028] In some embodiments, a first preset mass of the vehicle is obtained. The first mass is mass information that is stored in the vehicle control unit storage module in advance. The preset process can be calibrated and set when the vehicle leaves the factory, or determined by the user through a specified operation.

[0029] In some embodiments, a first moment is determined while the vehicle is in motion. This first moment is the first parameter detection moment selected during the vehicle's motion. Its selection does not depend on specific driving stage conditions, but only requires that the vehicle is in motion. It can be determined by the timing module of the on-board control unit according to preset rules, or by the detection system detecting and randomly selecting it in real time after the vehicle starts driving.

[0030] In some embodiments, at the first time, the vehicle is subjected to driving parameter collection by a special parameter detection assembly installed on the vehicle to obtain first driving parameters. Among them, the speed parameter is obtained by a wheel speed sensor integrated in the wheel hub and a satellite positioning module on the vehicle. The wheel speed sensor captures the wheel hub rotation period in real time and converts it into corresponding linear speed data, and the satellite positioning module synchronously receives positioning signals to calculate the instantaneous moving speed of the vehicle. After the data of the two is fused and corrected by the built-in algorithm of the vehicle control unit, the accurate speed parameter at the first time is obtained. The acceleration parameter is obtained by an inertial measurement unit fixed on the central position of the vehicle chassis. The high-precision acceleration sensor in the unit can sense the speed change rate of the vehicle in the driving direction in real time. After the interference signal is eliminated by the filtering circuit, the instantaneous acceleration parameter at the first time is output. In addition, the first driving parameters also include other auxiliary parameters related to the driving state of the vehicle to constitute a complete first-time driving parameter set and provide comprehensive data support for subsequent quality update calculation.

[0031] As an example, taking the urban road driving scenario of a domestic pure electric sedan as an example, the following is a detailed description: a first mass preset for the vehicle is obtained, which is the mass data stored in the vehicle central control unit after the vehicle is factory-calibrated by the manufacturer through professional equipment, and specifically the sum of the curb mass of the electric sedan and the mass of the power battery pack and the tools carried under the standard configuration, the value is 1600 kg, which can be directly read and called through the storage module of the vehicle central control unit. Determine the first time during the driving process of the vehicle, specifically, the electric sedan is started by the driver after the power supply is started, and enters the urban secondary trunk road from the parking lot, and the vehicle central control unit detects the vehicle speed in real time during driving. When the vehicle speed remains in the interval of 30 km / h to 35 km / h for 10 seconds, the parameter detection instruction is triggered, and the time point corresponding to this time is the first time. At this time, the electric sedan is driving on the urban secondary trunk road without obvious slope and flat road surface, the traffic flow around is stable, and the driving state is stable. At this time, the first driving parameter is obtained by cooperating with the multiple detection components installed on the vehicle. Among them, the speed parameter is detected by the wheel speed sensor installed at the four wheel hubs of the electric sedan and the satellite positioning module on the roof. The wheel speed sensor collects the wheel hub rotation frequency in real time and converts it into a linear speed signal, and the satellite positioning module synchronously receives satellite positioning data to calculate the instantaneous moving speed of the vehicle. After the signals collected by the two are transmitted to the vehicle central control unit, the signal interference is eliminated by the filtering algorithm, and finally the speed parameter at this time is obtained as 32 km / h; the acceleration parameter is detected by the inertial measurement unit fixed on the central chassis of the electric sedan. The three-axis acceleration sensor built-in the inertial measurement unit only collects the acceleration signal in the driving direction (longitudinal direction) of the vehicle, and after signal amplification processing, the acceleration parameter at this time is obtained as 0.2 m / s2; in addition, the first driving parameter also includes the output torque parameter of the driving motor at this time, which is calculated by the motor controller after collecting the motor rotor speed, inverter output current and other data, the value is 90 Nm. The above speed, acceleration and driving motor output torque jointly constitute the first driving parameter at the first time.

[0032] In step 102, based on the first driving parameter, the first mass is updated to obtain the second mass of the vehicle.

[0033] ​In some embodiments, the second mass refers to an intermediate parameter reflecting the actual mass of the vehicle under its current driving state, obtained by correcting and updating the vehicle's pre-stored initial mass based on the driving parameters collected at the first detection moment. During the update process, the onboard central control unit calls upon core data such as the drive motor output torque and driving direction acceleration from the first driving parameters, and combines them with preset correction coefficients such as air resistance and road rolling resistance during vehicle movement. The initial mass is then calibrated using a constructed mass adjustment logic. Specifically, based on the power transmission relationship between the drive motor output torque and the vehicle acceleration, the difference between the initial mass and the mass under the vehicle's actual stress state is calculated. The initial mass is then adjusted in either a positive or negative direction to eliminate deviations caused by slight changes in vehicle load, equipment wear and tear, etc. The resulting calibrated mass data is the second mass. This mass data is closer to the vehicle's current actual mass state than the initial mass, providing a reliable intermediate benchmark for subsequent iterative updates based on driving parameters from multiple subsequent detection moments.

[0034] In some embodiments, see Figure 4 , Figure 4 This is a flowchart illustrating the vehicle mass determination method provided in the embodiments of this application. Figure 2 , Figure 3 Step 102 shown can be achieved through Figure 4 Steps 1021 to 1023 shown are implemented.

[0035] In step 1021, based on the first driving parameters, the mass of the vehicle is estimated to obtain the first reference mass of the vehicle at the first moment.

[0036] In some embodiments, the first reference quality refers to the actual quality of the vehicle at the first detection time, which is calculated based on the complete driving parameters collected at the first detection time, combined with the preset fixed physical parameters and known coefficients of the vehicle, through the constructed quality estimation logic. In the quality estimation process, the vehicle-mounted central control unit first extracts the driving parameters at the first detection time, which specifically include the vehicle longitudinal acceleration, longitudinal speed, road slope, and wheel-end driving torque. At the same time, the fixed physical parameters and preset coefficients pre-stored in the vehicle-mounted storage module are called, which include the wheel radius, air density, air resistance coefficient, vehicle frontal area, gravitational acceleration, and rolling resistance coefficient. Subsequently, the preset quality estimation logic is used for calculation. The wheel-end driving torque is first associated with the wheel radius to convert it into the basic driving force in the driving direction of the vehicle. Then, the air resistance determined by the longitudinal speed, air density, air resistance coefficient, and vehicle frontal area is deducted from the basic driving force, the rolling resistance determined by the gravitational acceleration, rolling resistance coefficient, and vehicle-related gravitational component is deducted, and the component of gravity along the road slope direction determined by the gravitational acceleration and road slope is deducted, to obtain the effective driving force in the driving direction of the vehicle. Finally, based on the corresponding relationship between the effective driving force and the longitudinal acceleration, the quality estimation result obtained is the first reference quality. The quality estimation value can reflect the actual quality state of the vehicle at the first detection time in real time, and provide an accurate initial real-time estimation benchmark for subsequent quality updating or further calibration work.

[0037] As an example, the expression of the first reference quality can be: (Formula 1); wherein, is used to indicate the first reference quality, and the first driving parameter includes is the longitudinal acceleration of the vehicle at the first time, is the longitudinal speed of the vehicle at the first time, is the road slope; is the wheel-end driving torque, is the wheel radius, is the air density, is the air resistance coefficient, is the vehicle frontal area, is the gravitational acceleration, is the rolling resistance coefficient.

[0038] In step 1022, the first reference quality and the first quality are compared to obtain a first comparison result, and the difference between the first reference quality and the first quality is compared with a quality threshold to obtain a second comparison result.

[0039] In some embodiments, the first comparison result is used to indicate whether the first reference quality is greater than the first quality, and the second comparison result is used to indicate whether the difference value is greater than the quality threshold.

[0040] In step 1023, the first quality is updated based on the first comparison result and the second comparison result to obtain a second quality of the vehicle.

[0041] In some embodiments, the second quality is a vehicle quality calibration parameter obtained by targeted calibration based on the reference quality of the vehicle at the first detection time, the pre-stored initial quality, and the preset quality threshold, and is used to provide an accurate and stable intermediate reference for iterative updating of subsequent vehicle quality. Before determining the second quality, first, a difference value between the reference quality and the initial quality is calculated, and then two comparison operations are sequentially performed: the first comparison operation is used to determine the size relationship between the reference quality and the initial quality to obtain a corresponding comparison result; and the second comparison operation is used to determine the size relationship between the difference value calculated above and the preset quality threshold to obtain another set of comparison results. According to different combinations of the two comparison results, a corresponding calibration mode is used to determine the second quality.

[0042] In some embodiments, the above step 1023 can also be implemented in the following manner: in response to the first comparison result indicating that the first reference quality is greater than the first quality, and the second comparison result indicating that the difference value is greater than the quality threshold, the sum of the first reference quality and the quality threshold is determined as the second quality; in response to the first comparison result indicating that the first reference quality is greater than the first quality, and the second comparison result indicating that the difference value is less than the quality threshold, the first reference quality is determined as the second quality; in response to the first comparison result indicating that the first reference quality is less than the first quality, and the second comparison result indicating that the difference value is greater than the quality threshold, the first reference quality minus the quality threshold is obtained as the second quality; and in response to the first comparison result indicating that the first reference quality is less than the first quality, and the second comparison result indicating that the difference value is less than the quality threshold, the first reference quality is determined as the second quality.

[0043] In some embodiments, when the first comparison result shows that the value of the reference quality is greater than the value of the initial quality, and the second comparison result shows that the absolute value difference between the reference quality and the initial quality is greater than the quality threshold, it indicates that the reference quality has a positive deviation beyond a reasonable range relative to the initial quality. At this time, a positive compensation calibration mode is used to perform a summation operation on the value of the reference quality and the value of the quality threshold. The specific value obtained by the summation operation is the second quality after calibration.

[0044] In some embodiments, when the first comparison result shows that the value of the reference mass is greater than the value of the initial mass, and the second comparison result shows that the absolute value difference between the reference mass and the initial mass is less than the mass threshold, it indicates that the positive deviation of the reference mass relative to the initial mass is within a reasonable range, and no compensation calibration is needed. The value of the reference mass calculated at present is directly determined as the second mass.

[0045] In some embodiments, when the first comparison result shows that the value of the reference mass is less than the value of the initial mass, and the second comparison result shows that the absolute value difference between the reference mass and the initial mass is greater than the mass threshold, it indicates that the negative deviation of the reference mass relative to the initial mass is beyond a reasonable range. At this time, a negative compensation calibration method is used, and the value of the reference mass is subtracted from the value of the mass threshold. The specific value obtained by the subtraction operation is the second mass after calibration.

[0046] In some embodiments, when the first comparison result shows that the value of the reference mass is less than the value of the initial mass, and the second comparison result shows that the absolute value difference between the reference mass and the initial mass is less than the mass threshold, it indicates that the negative deviation of the reference mass relative to the initial mass is within a reasonable range, and no compensation calibration is needed. The value of the reference mass calculated at present is directly determined as the second mass. Through the above differential calibration logic based on the two comparison results, the real-time and stability of the reference mass can be effectively balanced, and the second mass can reflect the current actual mass state of the vehicle and avoid calibration deviation caused by parameter fluctuation.

[0047] As an example, the determination process of the second mass is described in detail taking the urban road driving scenario of a household pure electric car as an example. The initial mass of the vehicle is preset to be 1600 kg, and the mass threshold is preset to be 50 kg. The mass threshold is a fixed value stored in the vehicle central control unit in advance based on the driving stability requirements of the vehicle and the parameter detection accuracy, and is used to determine whether the deviation of the reference mass from the initial mass is beyond a reasonable range.

[0048] Continuing the previous example, at the first detection time of vehicle driving, the reference mass is calculated as 1720 kg by the parameter detection and mass estimation logic. At this time, the absolute value difference between the reference mass and the initial mass is first calculated, i.e. 1720 kg minus 1600 kg to obtain 120 kg. Then two comparison operations are performed. The first comparison result shows that the value of the reference mass is greater than the value of the initial mass, and the second comparison result shows that the difference of 120 kg is greater than the mass threshold of 50 kg, which meets the condition that the reference mass is greater than the initial mass and the difference exceeds the reasonable range. At this time, the positive compensation calibration mode is adopted, and the reference mass of 1720 kg is summed with the mass threshold of 50 kg to obtain a calculation result of 1770 kg, which is the second mass. This scenario corresponds to the case where the vehicle is loaded with a large amount of goods, resulting in a significant increase in the actual mass, and the reference mass exceeds the reasonable range of the initial mass.

[0049] Continuing the previous example, if the reference mass calculated at the first detection time is 1630 kg, the absolute value difference between the reference mass and the initial mass is 30 kg. The first comparison result shows that the reference mass is greater than the initial mass, and the second comparison result shows that the difference of 30 kg is less than the mass threshold of 50 kg, which meets the condition that the reference mass is greater than the initial mass and the difference is within a reasonable range. No compensation calibration is required, and the reference mass of 1630 kg is directly determined as the second mass. This scenario corresponds to the case where the vehicle is loaded with a small amount of goods, and the increase in the actual mass is within a reasonable fluctuation range.

[0050] Continuing the previous example, if the reference mass calculated at the first detection time is 1520 kg, the absolute value difference between the reference mass and the initial mass is 80 kg. The first comparison result shows that the value of the reference mass is less than the value of the initial mass, and the second comparison result shows that the difference of 80 kg is greater than the mass threshold of 50 kg, which meets the condition that the reference mass is less than the initial mass and the difference exceeds the reasonable range. At this time, the negative compensation calibration mode is adopted, and the reference mass of 1520 kg is subtracted from the mass threshold of 50 kg to obtain a calculation result of 1470 kg, which is the second mass. This scenario corresponds to the case where the vehicle unloads a large amount of goods, resulting in a significant decrease in the actual mass, and the reference mass is lower than the reasonable range of the initial mass.

[0051] In the above example, if the reference mass calculated at the first detection time is 1570 kg, the absolute value difference between the reference mass and the initial mass is 30 kg. The first comparison result shows that the reference mass is less than the initial mass, and the second comparison result shows that the difference of 30 kg is less than the mass threshold of 50 kg, which meets the condition that the reference mass is less than the initial mass and the difference is within a reasonable range, so no compensation calibration is needed, and the reference mass of 1570 kg is directly determined as the second mass. The scenario corresponds to the case where the vehicle unloads a small amount of goods, and the actual mass decreases within a reasonable fluctuation range.

[0052] In this way, by executing differentiated second mass determination logic based on the size relationship between the reference mass and the initial mass, and the size relationship between the difference between the two and the mass threshold, the different amplitude changes in the actual mass of the vehicle caused by loading or unloading goods can be accurately adapted. When the deviation between the reference mass and the initial mass is within a reasonable range, the reference mass is directly used to ensure that the mass data can reflect the current actual state of the vehicle in real time, and when the deviation exceeds the reasonable range, targeted compensation calibration operation is performed to effectively filter abnormal fluctuations or detection deviations that may exist in the reference mass, avoid distortion of subsequent mass update results due to single mass data deviation, significantly improve the accuracy and stability of vehicle mass calibration, and provide accurate and reliable intermediate reference data for subsequent mass iterative update based on driving parameters at multiple subsequent detection times, thereby optimizing the control accuracy of vehicle power control, energy management and other related systems, and ensuring that the vehicle can maintain good driving performance under different mass states.

[0053] In this way, by estimating the mass based on the real-time driving parameters at the first detection time of the vehicle to obtain the reference mass, the mass evaluation data can closely match the current actual driving state of the vehicle, avoiding evaluation lag caused by relying on a single preset initial mass. Subsequently, through the double comparison operation of comparing the reference mass with the initial mass and comparing the difference between the two with the preset mass threshold, the deviation degree and reasonableness of the reference mass relative to the initial mass can be accurately defined, and the initial mass is updated based on the double comparison result to obtain the second mass, which not only realizes dynamic calibration of the initial mass, but also filters abnormal data interference caused by detection errors or transient driving state fluctuations through reasonable deviation judgment logic, significantly improving the accuracy and real-time performance of vehicle mass data, providing reliable reference support for further iterative optimization of vehicle mass, and thereby helping to improve the control accuracy of vehicle power distribution, energy control, safety braking and other core systems, ensuring that the vehicle can maintain stable and efficient driving performance under different load states.

[0054] In step 103, the vehicle is detected for parameters at a plurality of second time points during the driving of the vehicle, to obtain second driving parameters of the vehicle at each of the second time points, the second time points being later than the first time point.

[0055] In some embodiments, the second driving parameters at different second time points are different, and a plurality of subsequent detection time points later than the first detection time point are selected during the continuous driving of the vehicle, the selection of the subsequent detection time points being triggered by the on-board central control unit according to a preset interval rule, which can be dynamically adjusted according to the driving road conditions of the vehicle, for example, triggered at an interval of 10 seconds when driving on urban roads, and triggered at an interval of 20 seconds when driving on highways, to ensure that the vehicle is in a stable driving state at each subsequent detection time point, without abnormal working conditions such as sudden acceleration, sudden deceleration, or sharp turning. At each subsequent detection time point, parameter acquisition is completed by the same parameter detection components as the first detection time point to obtain the driving parameters at the corresponding time point. Among them, the speed parameter is detected by the wheel speed sensor installed at the four wheel hubs of the vehicle and the satellite positioning module on the roof. The wheel speed sensor collects the wheel hub rotation frequency in real time and converts it into a linear speed signal, and the satellite positioning module synchronously receives satellite positioning data to calculate the instantaneous moving speed of the vehicle. After the signals are transmitted to the on-board central control unit, the interference is eliminated by filtering algorithm to obtain accurate speed parameters at each subsequent detection time point; the acceleration parameter is detected by the inertial measurement unit fixed on the central part of the vehicle chassis. The three-axis acceleration sensor built-in this unit only collects the vehicle longitudinal acceleration signal, which is outputted after signal amplification and noise reduction processing to obtain the instantaneous acceleration parameter at each subsequent detection time point; the driving motor output torque parameter is calculated by the motor controller to collect the motor rotor speed, inverter output current and other data, and the road slope parameter at each subsequent detection time point is also collected by the on-board tilt sensor and transmitted to the on-board central control unit. Through the above detection operation, the driving parameter set containing speed, acceleration, driving motor output torque, road slope and other parameters corresponding to each subsequent detection time point is obtained, and this driving parameter set is the driving parameter at each subsequent detection time point.

[0056] In step 104, the second quality is iteratively updated based on the second driving parameters at the second time points, to obtain the target quality of the vehicle.

[0057] In some embodiments, the target mass refers to a final mass parameter that is finally determined after multiple iterative updating and optimization of the intermediate mass after the first calibration, and can accurately reflect the current actual mass state of the vehicle, based on the driving parameters collected at multiple subsequent detection moments later than the first detection moment during the driving process of the vehicle. The determination process is realized through iterative updating logic in time sequence, specifically, the first iterative updating of the intermediate mass is performed by substituting the driving parameters collected at the first subsequent detection moment into the preset mass updating algorithm to generate the corresponding intermediate target mass; then for each subsequent detection moment, the iterative updating operation is performed based on the intermediate target mass corresponding to the previous subsequent detection moment and the driving parameters collected at the current subsequent detection moment, that is, the intermediate target mass obtained by the previous iteration is corrected for deviation by using the speed, acceleration, driving motor output torque and other core data in the current driving parameters to generate the intermediate target mass corresponding to the current moment, and all subsequent detection moments are arranged in time sequence, and the subsequent detection moment is always later than the previous detection moment; after completing the iterative updating operation corresponding to the last subsequent detection moment, the intermediate target mass obtained at this time is directly determined as the target mass of the vehicle. Through multiple iterative updating, the errors that may exist in the single parameter detection or single updating process can be gradually eliminated, so that the target mass obtained finally is closer to the actual mass of the vehicle, and reliable mass data support is provided for the accurate control of the core systems such as vehicle power control, energy consumption optimization and safety braking.

[0058] In some embodiments, referring to Figure 5 , Figure 5 is a flowchart of a mass determination method of a vehicle provided by the embodiments of the present application Figure 3 , Figure 3 The step 104 shown in FIG. 4 can be implemented by steps 1041 to 1043 shown in FIG. 4. Figure 5

[0059] In step 1041, the second mass is updated based on the second driving parameters of the first second moment to obtain the first target mass of the vehicle.

[0060] ​In some embodiments, the updating of the second mass based on the second driving parameter at the first second time to obtain the first target mass of the vehicle can be achieved by: performing mass estimation on the vehicle based on the second driving parameter at the first second time to obtain a second reference mass of the vehicle at the first second time; comparing the second reference mass at the first second time with the second mass to obtain a third comparison result, and comparing the difference between the second mass and the second reference mass at the first second time with a mass threshold to obtain a fourth comparison result; and updating the second mass based on the third comparison result and the fourth comparison result to obtain the first target mass.

[0061] In some embodiments, the intermediate mass after the first calibration is updated based on the driving parameter collected at the first subsequent detection time to obtain the first intermediate target mass in the following specific process: first, mass estimation is performed based on the driving parameter at the subsequent detection time, the driving parameter includes core data such as longitudinal acceleration, longitudinal speed, road slope, wheel end driving torque, and fixed parameters and coefficients such as wheel radius, air density, air resistance coefficient, wind area, gravitational acceleration, and rolling resistance coefficient in the vehicle-mounted storage module are called, and the reference mass corresponding to the subsequent detection time is calculated through the same estimation logic as the reference mass at the first detection time. Subsequently, two comparison operations are performed, the first comparison operation is to compare the reference mass at the subsequent detection time with the current intermediate mass in terms of numerical value to generate a comparison result indicating the size relationship between the two; the second comparison operation is to first calculate the absolute value difference between the reference mass at the subsequent detection time and the intermediate mass, and then compare the calculated difference with a preset mass threshold in terms of numerical value to generate a comparison result indicating whether the difference exceeds a reasonable range, wherein the mass threshold and the threshold for judging the difference at the first detection time remain the same to ensure the uniformity of the judgment standard. Finally, based on the combination of the two comparison results, the current intermediate mass is updated using the same differentiated updating logic as the determination of the intermediate mass, if the reference mass is greater than the intermediate mass and the difference is greater than the mass threshold, the sum of the reference mass and the mass threshold is taken as the update result; if the reference mass is greater than the intermediate mass and the difference is less than the mass threshold, the reference mass is directly taken as the update result; if the reference mass is less than the intermediate mass and the difference is greater than the mass threshold, the difference between the reference mass and the mass threshold is taken as the update result; if the reference mass is less than the intermediate mass and the difference is less than the mass threshold, the reference mass is directly taken as the update result, which is the first intermediate target mass.

[0062] In some embodiments, the updating of the second quality based on the third comparison result and the fourth comparison result to obtain the first target quality can be achieved by the following manners: in response to the third comparison result indicating that the second reference quality is greater than the second quality and the fourth comparison result indicating that the difference value is greater than the quality threshold, determining the sum of the second reference quality and the quality threshold as the first target quality; in response to the third comparison result indicating that the second reference quality is greater than the second quality and the fourth comparison result indicating that the difference value is less than the quality threshold, determining the second reference quality as the first target quality; in response to the third comparison result indicating that the second reference quality is less than the second quality and the fourth comparison result indicating that the difference value is greater than the quality threshold, determining the second reference quality minus the quality threshold as the first target quality; and in response to the third comparison result indicating that the second reference quality is less than the second quality and the fourth comparison result indicating that the difference value is less than the quality threshold, determining the second reference quality as the first target quality.

[0063] In some embodiments, in the process of updating the intermediate quality based on the two comparison results to obtain the first intermediate target quality, the specific content of the two comparison results is first determined, wherein the first comparison result is used to indicate the value size relationship between the reference quality at the subsequent detection moment and the intermediate quality, and the second comparison result is used to indicate the value size relationship between the absolute value difference between the reference quality and the intermediate quality and the preset quality threshold value, and the quality threshold value is consistent with the threshold value used for judging the difference before, so as to ensure the uniformity of the judgment standard. When the first comparison result shows that the value of the reference quality is greater than the value of the intermediate quality, and the second comparison result shows that the absolute value difference between the two is greater than the quality threshold value, it indicates that the reference quality deviates positively from the intermediate quality beyond a reasonable range, and at this time, the value of the reference quality is summed with the value of the quality threshold value, and the specific value obtained by the operation is the first intermediate target quality. When the first comparison result shows that the value of the reference quality is greater than the value of the intermediate quality, and the second comparison result shows that the absolute value difference between the two is less than the quality threshold value, it indicates that the positive deviation of the reference quality from the intermediate quality is within a reasonable range, and no compensation calibration is needed, and the value of the reference quality is directly determined as the first intermediate target quality. When the first comparison result shows that the value of the reference quality is less than the value of the intermediate quality, and the second comparison result shows that the absolute value difference between the two is greater than the quality threshold value, it indicates that the reference quality deviates negatively from the intermediate quality beyond a reasonable range, and at this time, the value of the reference quality is subtracted from the value of the quality threshold value, and the specific value obtained by the operation is the first intermediate target quality. When the first comparison result shows that the value of the reference quality is less than the value of the intermediate quality, and the second comparison result shows that the absolute value difference between the two is less than the quality threshold value, it indicates that the negative deviation of the reference quality from the intermediate quality is within a reasonable range, and no compensation calibration is needed, and the value of the reference quality is directly determined as the first intermediate target quality.

[0064] In step 1042, the following processing is performed for iteration i: based on the second driving parameter at the i-1th second moment, the i-1th target quality is updated to obtain the i th target quality.

[0065] In some embodiments, N is used to indicate the total number of the second moments, and the i th second moment is later than the i-1th second moment.

[0066] In some embodiments, in the iteration process, for each iteration step with a serial number greater than 1 and not more than the total number of the second time points, the following process is performed. The second time point corresponding to the iteration step is later than the previous second time point, ensuring that the two detections are sequentially progressive in time. First, the driving parameter collected at the previous second time point is obtained, which includes the longitudinal speed, longitudinal acceleration, road slope, driving motor output torque and other quantitative indicators related to the vehicle driving state at the previous time point. Based on the driving parameter at the previous second time point, the same mass estimation logic as the first subsequent detection time point is used for calculation, that is, the reference mass corresponding to the previous second time point is obtained by combining the preset fixed parameters and coefficients such as wheel radius, air density, air resistance coefficient, wind area, gravitational acceleration, rolling resistance coefficient, etc. Then, the reference mass is compared with the target mass obtained in the last iteration for the first time to determine the numerical size relationship between the two; at the same time, the absolute value difference between the reference mass and the target mass obtained in the last iteration is calculated, and the difference is compared with the preset mass threshold for the second time to determine whether the difference exceeds a reasonable range, wherein the mass threshold remains the same as the threshold used in the previous steps to ensure uniformity of the judgment standard. Finally, according to the combination of the results of the two comparisons, the target mass obtained in the previous iteration is updated according to the same update logic as the determination of the first intermediate target mass: if the reference mass is greater than the target mass of the last iteration and the difference is greater than the mass threshold, the sum of the reference mass and the mass threshold is taken as the target mass of the current iteration; if the reference mass is greater than the target mass of the last iteration and the difference is less than the mass threshold, the reference mass is directly taken as the target mass of the current iteration; if the reference mass is less than the target mass of the last iteration and the difference is greater than the mass threshold, the difference between the reference mass and the mass threshold is taken as the target mass of the current iteration; if the reference mass is less than the target mass of the last iteration and the difference is less than the mass threshold, the reference mass is directly taken as the target mass of the current iteration, and the result obtained through the above process is the target mass corresponding to the current iteration step.

[0067] In some embodiments, the above-mentioned updating the i-1th target mass based on the second driving parameter at the i-1th second time point to obtain the i th target mass can be achieved by the following way: estimating the mass of the vehicle based on the second driving parameter at the i-1th second time point to obtain the second reference mass of the vehicle at the i-1th second time point; comparing the second reference mass with the i-1th target mass to obtain a third comparison result, and comparing the difference between the second reference mass and the i-1th target mass with a mass threshold to obtain a fourth comparison result; updating the i-1th target mass based on the third comparison result and the fourth comparison result to obtain the i th target mass.

[0068] In some embodiments, based on the driving parameters collected at the i-1th second time, the mass of the vehicle is estimated to obtain the reference mass corresponding to the time, and the driving parameters called in the process include the core data of the longitudinal acceleration, the longitudinal speed, the road slope, the driving motor output torque, etc. at the i-1th second time, and at the same time, the fixed parameters and coefficients such as the wheel radius, the air density, the air resistance coefficient, the windward area, the gravitational acceleration, and the rolling resistance coefficient in the vehicle-mounted storage module are called, and the same logic as the mass estimation of each previous time is used for calculation to obtain the reference mass corresponding to the i-1th second time. Then two comparison operations are performed, the first comparison operation is to compare the numerical values of the reference mass and the i-1th target mass, and generate a comparison result indicating the size relationship between the two; the second comparison operation is to first calculate the absolute value difference between the reference mass and the i-1th target mass, and then compare the difference with the preset mass threshold value, and generate a comparison result indicating whether the difference exceeds the reasonable range, wherein the mass threshold value is consistent with the threshold value used in the previous steps, ensuring the uniformity of the judgment standard. Finally, based on the combination of the above two comparison results, the i-1th target mass is updated using the same differentiated updating logic as the update of the first intermediate target mass, if the reference mass is greater than the i-1th target mass and the difference is greater than the mass threshold value, the sum of the reference mass and the mass threshold value is taken as the update result; if the reference mass is greater than the i-1th target mass and the difference is less than the mass threshold value, the reference mass is directly taken as the update result; if the reference mass is less than the i-1th target mass and the difference is greater than the mass threshold value, the difference between the reference mass and the mass threshold value is taken as the update result; if the reference mass is less than the i-1th target mass and the difference is less than the mass threshold value, the reference mass is directly taken as the update result, which is the i th target mass.

[0069] As an example, taking the urban expressway driving scene of a household pure electric car as an example, the determination method of the i th target mass in the iteration process is specifically explained, wherein the i-1th target mass obtained by the vehicle after the i-1th iteration is 1700 kg, the preset mass threshold value is 50 kg, which is consistent with the threshold value used in the previous steps, and the i-1th second time is when the vehicle drives to the straight section of the expressway and is in a stable uniform speed state. At the i-1th second time, through the cooperative detection of the wheel speed sensor, the satellite positioning module, the inertial measurement unit, the motor controller and the inclination sensor, the driving parameters including the longitudinal speed of 45 km / h, the longitudinal acceleration of 0.1 m / s2, the driving motor output torque of 75 N·m, the road slope of 0.1%, the wheel radius of 0.3 m, the air density of 1.2 kg / m3, the air resistance coefficient of 0.3, the windward area of 2 m2, the gravitational acceleration of 9.8 m / s2, and the rolling resistance coefficient of 0.01 are obtained. The second reference mass is calculated based on the second driving parameter, the preset fixed parameters such as wheel radius, air density, air resistance coefficient, and the same mass estimation logic as before.

[0070] Continuing the previous example, if the calculated second reference mass is 1780 kg, at this time, 1780 kg is compared with the i-1 target mass 1700 kg, the third comparison result shows that the second reference mass is greater than the i-1 target mass, and the difference between the two is 80 kg, which is compared with the mass threshold 50 kg, the fourth comparison result shows that the difference is greater than the mass threshold, based on the combination result, 1780 kg and 50 kg are summed up to get 1830 kg, which is the i target mass, corresponding to the scene that the vehicle loads a large amount of goods in the middle of the journey, resulting in a significant increase in mass.

[0071] Continuing the previous example, if the calculated second reference mass is 1730 kg, the third comparison result shows that the second reference mass is greater than the i-1 target mass, and the difference between the two is 30 kg, the fourth comparison result shows that the difference is less than the mass threshold, at this time, 1730 kg is directly determined as the i target mass, corresponding to the scene that the vehicle loads a small amount of goods and the increase in mass is within a reasonable range.

[0072] Continuing the previous example, if the calculated second reference mass is 1620 kg, the third comparison result shows that the second reference mass is less than the i-1 target mass, and the difference between the two is 80 kg, the fourth comparison result shows that the difference is greater than the mass threshold, based on the combination result, 1620 kg is subtracted by 50 kg to get 1570 kg, which is the i target mass, corresponding to the scene that the vehicle unloads a large amount of goods in the middle of the journey, resulting in a significant decrease in mass.

[0073] Continuing the previous example, if the calculated second reference mass is 1670 kg, the third comparison result shows that the second reference mass is less than the i-1 target mass, and the difference between the two is 30 kg, the fourth comparison result shows that the difference is less than the mass threshold, at this time, 1670 kg is directly determined as the i target mass, corresponding to the scene that the vehicle unloads a small amount of goods and the decrease in mass is within a reasonable range.

[0074] Thus, by estimating the corresponding reference quality based on the real-time driving parameter estimation at the previous subsequent detection moment, combining the size relationship between the reference quality and the target quality obtained in the last iteration, and the comparison result between the difference value and the quality threshold, the target quality of the previous iteration is updated to obtain the target quality of the current iteration, which can make the target quality of each iteration closely follow the dynamic changes of the actual vehicle mass, capture the subtle fluctuations of the mass through real-time parameter estimation, effectively filter the errors or transient disturbances that may exist in single detection through double comparison logic, and avoid distortion of the mass update result due to single time data deviation. In the multiple iteration process, the target quality at the next moment is always optimized based on the target quality at the previous moment, so that the mass data gradually converges to the actual mass level of the vehicle in dynamic adjustment, significantly improving the accuracy and stability of the target mass, providing reliable mass parameter support for the precise implementation of core functions such as vehicle power distribution, energy consumption control, and braking distance calculation, and ensuring efficient and safe operation performance of the vehicle under different load states and driving conditions.

[0075] In step 1043, a target mass of the vehicle is determined based on the Nth target mass.

[0076] In some embodiments, the target mass refers to the final mass parameter that can accurately reflect the stable mass state of the vehicle, which is finally determined by calculating the mass change rate in the iteration process and combining the preset threshold. The determination process first needs to calculate the mass change rate in the multiple iteration update process, which is used to quantify the fluctuation amplitude or change trend of all intermediate target masses with the progress of iteration steps, and can be obtained by calculating the mean value of the absolute value of the difference between adjacent intermediate target masses, or by calculating the ratio of the extreme difference value of all intermediate target masses to the number of iterations, which can intuitively reflect the stability of the mass update process. Then, the calculated mass change rate is compared with the preset change rate threshold to obtain a comparison result for judging whether the mass change is within the stable range, wherein the change rate threshold is a fixed parameter pre-stored in the vehicle control unit and set based on the vehicle mass detection accuracy requirement and driving stability requirement. Finally, the target mass is determined according to the comparison result: if the mass change rate is less than or equal to the change rate threshold, it indicates that the mass data has stabilized in the iteration process, and the intermediate target mass obtained in the last iteration can be directly determined as the target mass; if the mass change rate is greater than the change rate threshold, it indicates that the mass data still fluctuates beyond the allowed range, and the statistical mean or weighted value of all intermediate target masses is used as the target mass to ensure that the final target mass can avoid the influence of single iteration error and accurately reflect the actual stable mass state of the vehicle, providing reliable data support for core systems such as vehicle power control and energy optimization.

[0077] In some embodiments, the step 1043 can be implemented by determining a mass change rate of the vehicle in the iteration update process of the previous N masses based on the first target mass to the Nth target mass; comparing the mass change rate with a change rate threshold to obtain a fifth comparison result, and determining the target mass of the vehicle based on the fifth comparison result.

[0078] In some embodiments, based on all the intermediate target masses obtained through multiple iteration updates, the mass change rate of the vehicle in the iteration process is determined by the following process: first, extract the intermediate target mass value corresponding to each iteration, calculate the absolute value of the difference between the intermediate target masses obtained by adjacent iterations, i.e., the absolute value of the difference between the intermediate target mass of the latter iteration and the intermediate target mass of the former iteration, then sum all the absolute values of the adjacent differences, and divide the sum by the total number of adjacent differences (i.e., the total number of iterations minus one), to obtain the average value, which is the mass change rate. The smaller the value, the more stable the mass data is.

[0079] In some embodiments, the calculated mass change rate is compared with a preset change rate threshold to obtain a comparison result for determining whether the mass fluctuation is within the allowable range, wherein the change rate threshold is a fixed parameter pre-stored in the vehicle control unit, which is set based on the accuracy requirement of vehicle mass detection, the stability requirement of power system control, and the characteristics of actual driving conditions, for example, determined according to the mass fluctuation range of the vehicle in full load and empty load states and safety control standards.

[0080] In some embodiments, the target mass of the vehicle is determined based on the above comparison result: if the comparison result shows that the mass change rate is less than or equal to the change rate threshold, it indicates that the mass data fluctuation in the multiple iteration process is within a reasonable stable range, and the intermediate target mass obtained through the last iteration is directly determined as the target mass of the vehicle; if the comparison result shows that the mass change rate is greater than the change rate threshold, it indicates that the mass data still has fluctuations beyond the allowable range, and the arithmetic mean of all the intermediate target masses is calculated, and the average value is determined as the target mass of the vehicle. Through this way, the abnormal fluctuations in the iteration process can be effectively smoothed, ensuring that the final target mass is close to the actual mass state of the vehicle and has good stability, providing a reliable mass parameter basis for the subsequent power distribution, energy management and other core control logic of the vehicle.

[0081] In some embodiments, the quality change rate refers to a parameter obtained through specific statistical calculation based on all intermediate target qualities generated in the multiple iteration updating process of the vehicle quality, for quantifying the overall fluctuation amplitude or change trend of the quality data in the iteration process. Its calculation is based on all intermediate target qualities, and is usually obtained by extracting the intermediate target qualities corresponding to the adjacent two iterations, calculating the absolute value of the difference between the two, and then statistically processing (such as calculating the average value, calculating the ratio, etc.) all adjacent difference absolute values. It can directly reflect the stability degree of the quality data in the multiple iteration process — the smaller the value, the smaller the fluctuation of the quality data in the iteration process, and the more stable it is; the larger the value, the more intense the fluctuation of the quality data, and it has not yet reached a stable state. This parameter is the core basis for judging whether the iteration quality data meets the target quality determination condition, and provides quantitative support for subsequent comparison with the preset change rate threshold and then accurate determination of the final target quality of the vehicle.

[0082] As an example, the determination process of the target quality is described in detail taking the continuous driving scene of a household pure electric sedan on an urban expressway as an example, in which the vehicle obtains 5 intermediate target qualities through multiple iteration updates, which are 1720 kg, 1730 kg, 1725 kg, 1728 kg and 1726 kg, and the preset change rate threshold is 8 kg, which is pre-stored in the vehicle central control unit based on the vehicle quality detection accuracy requirement and the power control stability standard. First, calculate the quality change rate in the iteration process. After extracting all the intermediate target qualities, the absolute value of the difference between the adjacent two intermediate target qualities is calculated in turn: the absolute value of the difference between 1730 kg and 1720 kg is 10 kg, the absolute value of the difference between 1725 kg and 1730 kg is 5 kg, the absolute value of the difference between 1728 kg and 1725 kg is 3 kg, and the absolute value of the difference between 1726 kg and 1728 kg is 2 kg; then the sum of the above 4 difference absolute values is 20 kg, and divided by the total number of adjacent differences 4, the average value is 5 kg, which is the quality change rate. Compare the calculated quality change rate of 5 kg with the change rate threshold of 8 kg, and get the comparison result that the quality change rate is less than the change rate threshold, which indicates that the fluctuation of the quality data in the iteration process is within a reasonable stable range, and at this time the intermediate target quality of 1726 kg obtained by the last iteration is directly determined as the target quality of the vehicle.

[0083] Thus, by determining the quality change rate in the iteration process based on the intermediate target quality generated by multiple iteration updates, the fluctuation amplitude of the quality data with the iteration advancement can be accurately quantified, and it can be intuitively judged whether the quality update tends to be stable. Then, the quality change rate is compared with the preset change rate threshold, and the target quality is determined according to the comparison result. This not only avoids the problem of insufficient accuracy caused by unstable fluctuations of the last iteration quality, but also avoids the defect of response lag of the latest quality state caused by blindly taking the average of all intermediate qualities. When the quality change rate is within the threshold range, the last iteration quality is used to ensure that the target quality conforms to the latest actual state of the vehicle. When the quality change rate exceeds the threshold, the average smoothing fluctuation error is used to significantly improve the accuracy and reliability of the target quality, providing accurate and stable quality parameter support for core systems such as vehicle power distribution, energy optimization, and brake control, and ensuring that the vehicle can maintain efficient and safe operation performance under different driving conditions and load states.

[0084] In some embodiments, the above-mentioned determining the target quality of the vehicle based on the fifth comparison result can be achieved by the following manner: in response to the fifth comparison result indicating that the quality change rate is less than the change rate threshold, determining the target quality of the vehicle as the Nth target quality; and in response to the fifth comparison result indicating that the quality change rate is greater than or equal to the change rate threshold, iteratively updating the Nth target quality based on the third driving parameter of the vehicle at at least one third time point until the quality change rate of the vehicle after the second time point is less than the change rate threshold, and determining the updated Nth target quality of the corresponding iteration round as the target quality of the vehicle, the third time point being later than the second time point.

[0085] In some embodiments, when the fifth comparison result shows that the value of the quality change rate is less than the value of the change rate threshold, it indicates that the fluctuation of the quality data in the multiple iteration update process has been within a stable range, and there is no need for further adjustment. At this time, the Nth target quality obtained through the last iteration is directly determined as the target quality of the vehicle, which can accurately reflect the current stable actual quality state of the vehicle. When the fifth comparison result shows that the value of the quality change rate is greater than or equal to the value of the change rate threshold, it indicates that the previous iteration update has not made the quality data reach a stable state, and additional iteration update operation is needed. A plurality of third time points later than all the second time points are selected, and the third time points are triggered at a preset time interval. The interval length can be dynamically adjusted according to the driving conditions of the vehicle to ensure that the vehicle is in a stable driving state at each third time point. At each third time point, the driving parameters are collected by the same parameter detection component as the second time point, and the parameters include the third driving parameters such as the longitudinal speed, the longitudinal acceleration, the road slope, and the driving motor output torque at the third time point. Based on the third driving parameters at each third time point, the same logic as updating the ith target quality is used to iteratively update the current Nth target quality: first, the reference quality at the corresponding time point is estimated based on the third driving parameters, then the reference quality is compared with the target quality of the current iteration, the difference between the two is calculated and compared with the quality threshold, and the current target quality is updated according to the comparison result to generate a new target quality. The above iteration update process based on the third time driving parameters is repeated, and the quality change rate corresponding to each new iteration step is continuously calculated until the value of the quality change rate is less than the value of the change rate threshold. At this time, the target quality obtained after this round of iteration update is determined as the final target quality of the vehicle, and through this way, the final target quality can not only reflect the latest actual quality state of the vehicle, but also have sufficient stability.

[0086] Thus, by differentiating the target mass according to the comparison result of the mass change rate and the change rate threshold, the mass obtained by the last iteration is directly used when the mass change rate is less than the threshold and the iteration data has tended to be stable, ensuring that the target mass can accurately fit the latest actual mass state of the vehicle and avoiding response lag of real-time mass due to excessive processing; when the mass change rate is greater than or equal to the threshold and the iteration data has not yet stabilized, the iteration update is continued with the newly added detection parameters later than the original detection time until the mass change rate meets the stable condition to determine the target mass, effectively filtering the possible persistent fluctuations in the early iteration process and avoiding the influence of unstable data on the accuracy of the target mass. This method can flexibly adjust the iteration process according to the actual stable state of mass update, without fixed iteration rounds causing redundant calculation, and can ensure the stability and reliability of the target mass through dynamic supplementary iteration, providing accurate and stable mass parameter support for core systems such as vehicle power distribution, energy optimization, and brake control, and ensuring efficient and safe operation performance of the vehicle under complex scenarios such as load changes and road condition fluctuations.

[0087] Thus, by first obtaining the initial mass of the vehicle preset, and then using the real-time driving parameters at the first time of vehicle driving to update the initial mass to obtain the intermediate mass, the problem of large deviation from the actual mass of the vehicle caused by relying only on the preset initial mass is avoided, and then the real-time driving parameters collected at multiple subsequent driving times later than the first time are used to update the intermediate mass to obtain the target mass. The real-time driving parameters at multiple subsequent times can comprehensively capture the dynamic changes of the mass during vehicle driving, effectively covering the mass fluctuation characteristics under different driving conditions, and the iterative update process can gradually filter the errors that may exist in single parameter detection and the deviations caused by single update, so that the mass data gradually converges to the actual mass state of the vehicle in multiple rounds of calibration. The progressive mass update logic from initial calibration to multiple rounds of iterative optimization can layer by layer correct the deviation between the mass data and the actual mass, significantly reducing the influence of various interference factors on mass evaluation, thereby effectively improving the accuracy of the mass of the vehicle.

[0088] Next, an exemplary application of the embodiments of the present application in an actual application scenario of a pure electric vehicle will be described.

[0089] The convergence strategy of the vehicle weight estimation is reset. The vehicle weight is updated in a self-learning manner of sequential increase and decrease. At the same time, the vehicle weight update period is set, and the vehicle door state and vehicle speed condition are introduced into the update period of the vehicle weight estimation, avoiding frequent jumping of the vehicle weight. To a certain extent, the unreliability caused by one-time update result can be avoided. Sequential increase makes the result have high reliability. At the same time, the jumping of the vehicle weight update result is avoided. More accurate estimation of the vehicle weight can be achieved, which greatly improves the control and braking performance of the vehicle. At the same time, the energy distribution and energy consumption of the vehicle are greatly improved. The maneuverability, stability and driving comfort of the vehicle are improved. People are provided with safer, more comfortable and easier to control cars, promote the continuous development of automobile technology, and promote the continuous progress of the automobile industry, and help the vigorous development of social economy. The convergence strategy of the vehicle weight estimation is reset. The vehicle weight is updated in a self-learning manner of sequential increase and decrease. At the same time, the vehicle weight update period is set, and the vehicle door state and vehicle speed condition are introduced into the update period of the vehicle weight estimation, avoiding frequent jumping of the vehicle weight.

[0090] The existing sensor information of the vehicle is collected, including the actual torque of the motor, the actual braking torque of the wheel, and the longitudinal acceleration of the vehicle. Through the following formula and known information, the mass is preliminarily estimated.

[0091] According to the vehicle longitudinal dynamic model, the following relationship can be obtained: (Formula 2); Among them: is the acceleration resistance, is the driving force, is the air resistance, is the rolling resistance, is the slope resistance.

[0092] The above relationship can be expanded as follows: (Formula 3); Among them: m is the vehicle mass, a is the vehicle longitudinal acceleration, is the wheel end driving torque, is the wheel radius, is the air density, is the air resistance coefficient, is the vehicle frontal area, V is the vehicle longitudinal speed, G is the gravitational acceleration, f is the rolling resistance coefficient, is the road slope.

[0093] In order to avoid the deviation of the calculation result caused by unreasonable sampling points in the calculation process, the reasonable sampling points of acceleration and force are set, and only when the sampled data reaches the specified number, it is considered that the sampling point meets the convergence condition. Given an initial value of mass (for example, 2400 kg), when the calculation conditions (such as vehicle speed, acceleration value, and force value are within the calculation range) are met, the result calculated by the sampled point is greater than the current value, and the difference is greater than a fixed value (for example, 20 kg), then the fixed value (for example, 20 kg) is added to the current base value, if it is greater than the current value, but the difference is less than the fixed value, then the result is updated to the result of the current sampling point. When the calculation conditions are met, the result calculated by the sampled point is less than the current value, and the difference is greater than a fixed value (for example, 20 kg), then the fixed value (for example, 20 kg) is subtracted from the current base value, if it is less than the current value, but the difference is less than the fixed value, then the result is updated to the result of the current sampling point. If the sampling point is always in the same acceleration and force condition, it is considered that multiple values are sampled at the current sampling point, and the above method can be used for superposition. The sampling point needs to meet different acceleration and force points, and reach a certain number (which can be marked). When the above conditions are met and the mass change rate is less than a certain threshold, it is considered that the calculation converges. The mass of the vehicle is reset to the default initial value state each time the vehicle experiences an electric shock. The vehicle has a change in the door state each time, and the vehicle speed changes from 0 to a certain value and then to 0, which is considered as a mass estimation period. In each mass estimation period, the mass estimation is only allowed to update once.

[0094] In this way, the convergence condition of mass estimation is further processed, and the result is updated in the form of sequential increase or decrease, rather than directly updating the result to the calculation value at once. The result is more accurate. It can solve the problem of inaccurate vehicle mass estimation, provide more accurate information input for vehicle control, and improve the handling stability, comfort, safety and other performances of the whole vehicle. The convergence condition of vehicle mass estimation is re-adjusted, and the vehicle mass is sequentially increased or decreased by using a self-learning method. At the same time, the vehicle mass estimation update period is created based on the door state and the vehicle speed. It can be applied to vehicle mass estimation in different scenes and working conditions, and has wide applicability and flexibility. For example, it can be applied to driving working conditions such as regular urban road sections, highways, and national roads. It is used for acceleration, braking, and steering conditions. In short, the embodiments of the present application have the advantages of accuracy, practicality, creativity, and adaptability, and can provide stable and reliable information input for vehicle control and better safety guarantee for people's travel.

[0095] The following continues to illustrate an exemplary structure of the implementation of the vehicle mass determination device 455 provided by the embodiments of the present application as a software module. In some embodiments, as shown in FIG. 6, the vehicle mass determination device 455 includes a mass estimation module 601, a mass update module 602, a mass reset module 603, and a mass estimation period determination module 604. Figure 2As shown, the software modules stored in the mass determination apparatus 455 of the vehicle in the memory 450 can include: a first detection module configured to obtain a first mass of the vehicle, and perform parameter detection on the vehicle at a first time during driving of the vehicle to obtain a first driving parameter of the vehicle at the first time; a first update module configured to update the first mass based on the first driving parameter to obtain a second mass of the vehicle; a second detection module configured to perform parameter detection on the vehicle at a plurality of second times during driving of the vehicle to obtain a second driving parameter of the vehicle at each of the second times, the second times being later than the first time; and a second update module configured to update the second mass based on the second driving parameter at the second times to obtain a target mass of the vehicle.

[0096] In some embodiments, the first update module is further configured to estimate a first reference mass of the vehicle based on the first driving parameter, compare the first reference mass with the first mass to obtain a first comparison result, and compare a difference between the first reference mass and the first mass with a mass threshold to obtain a second comparison result; and update the first mass based on the first comparison result and the second comparison result to obtain the second mass of the vehicle.

[0097] In some embodiments, the first update module is further configured to, in response to the first comparison result indicating that the first reference mass is greater than the first mass and the second comparison result indicating that the difference is greater than the mass threshold, determine a sum of the first reference mass and the mass threshold as the second mass; in response to the first comparison result indicating that the first reference mass is greater than the first mass and the second comparison result indicating that the difference is less than the mass threshold, determine the first reference mass as the second mass; in response to the first comparison result indicating that the first reference mass is less than the first mass and the second comparison result indicating that the difference is greater than the mass threshold, obtain the second mass by subtracting the mass threshold from the first reference mass; and in response to the first comparison result indicating that the first reference mass is less than the first mass and the second comparison result indicating that the difference is less than the mass threshold, determine the first reference mass as the second mass.

[0098] In some embodiments, the second update module is further configured to update the second mass based on the second driving parameter at the first second time to obtain a first target mass of the vehicle; and iteratively perform the following processing: update an i-1th target mass based on the second driving parameter at an i-1th second time to obtain an ith target mass, N is used to indicate the total number of the second time points, and the i th second time point is later than the (i-1) th second time point; and the target mass of the vehicle is determined based on the N th target mass.

[0099] In some embodiments, the second updating module is further configured to: perform mass estimation on the vehicle based on the second driving parameter of the (i-1) th second time point to obtain a second reference mass of the vehicle at the (i-1) th second time point; compare the second reference mass with the (i-1) th target mass to obtain a third comparison result, and compare a difference between the second reference mass and the (i-1) th target mass with a mass threshold to obtain a fourth comparison result; and update the (i-1) th target mass based on the third comparison result and the fourth comparison result to obtain the i th target mass.

[0100] In some embodiments, the second updating module is further configured to: determine a mass change rate of the vehicle in an iterative updating process of the previous N masses of the vehicle based on the 1 st target mass to the N th target mass; compare the mass change rate with a change rate threshold to obtain a fifth comparison result, and determine the target mass of the vehicle based on the fifth comparison result.

[0101] In some embodiments, the second updating module is further configured to: in response to the fifth comparison result indicating that the mass change rate is less than the change rate threshold, determine the target mass of the vehicle as the N th target mass; and in response to the fifth comparison result indicating that the mass change rate is greater than or equal to the change rate threshold, perform iterative updating on the N th target mass based on a third driving parameter of the vehicle at at least one third time point until the mass change rate of the vehicle after the second time point is less than the change rate threshold, and determine an updated N th target mass of a corresponding iterative round as the target mass of the vehicle, the third time point being later than the second time point.

[0102] The embodiments of the present application provide a computer program product, which includes a computer program or computer executable instructions stored in a computer readable storage medium. A processor of an electronic device reads the computer executable instructions or the computer program from the computer readable storage medium, and the processor executes the computer executable instructions or the computer program, so that the electronic device performs the mass determination method of the vehicle provided in the embodiments of the present application.

[0103] The embodiment of the present application provides a computer readable storage medium storing computer executable instructions or computer programs, wherein the computer executable instructions or computer programs are stored, and when the computer executable instructions or computer programs are executed by a processor, the processor executes a mass determination method of a vehicle provided by the embodiment of the present application, for example, as shown in the following. Figure 3 The mass determination method of the vehicle is shown.

[0104] In some embodiments, the computer readable storage medium can be FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disc, or CD-ROM, etc. memory; and can also be various electronic devices including one or any combination of the above memories.

[0105] In some embodiments, the computer executable instructions or computer programs can be in the form of programs, software, software modules, scripts or codes, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and can be deployed in any form, including being deployed as independent programs or being deployed as modules, components, subroutines or other units suitable for use in a computing environment.

[0106] As an example, the computer executable instructions or computer programs can but not necessarily correspond to files in a file system, can be stored in a part of a file storing other programs or data, for example, stored in one or more scripts in a hyper text markup language (HTML, Hyper Text Markup Language) document, stored in a single file dedicated to the program in question, or stored in multiple cooperative files (for example, files storing one or more modules, subroutines or code parts).

[0107] As an example, the computer executable instructions or computer programs can be deployed to be executed on one electronic device, or executed on multiple electronic devices located in one place, or executed on multiple electronic devices distributed in multiple places and interconnected through a communication network.

[0108] The above is only an embodiment of the present application, and is not used to limit the protection scope of the present application. Any modification, equivalent replacement and improvement made within the spirit and scope of the present application shall be included in the protection scope of the present application.

Claims

1. A method for determining the mass of a vehicle, characterized in that, The method includes: The vehicle's preset first mass is obtained, and at the first moment during the vehicle's driving process, the vehicle's parameters are detected to obtain the vehicle's first driving parameters at the first moment. Based on the first driving parameters, the first mass is updated to obtain the second mass of the vehicle; During the vehicle's driving process, parameters are detected at multiple second moments to obtain second driving parameters of the vehicle at each second moment, wherein the second moment is later than the first moment; Based on the second driving parameters at the second moment, the second mass is iteratively updated to obtain the target mass of the vehicle.

2. The method according to claim 1, characterized in that, The step of updating the first mass based on the first driving parameters to obtain the second mass of the vehicle includes: Based on the first driving parameters, the mass of the vehicle is estimated to obtain the first reference mass of the vehicle at the first moment; The first reference quality is compared with the first quality to obtain a first comparison result, and the difference between the first reference quality and the first quality is compared with a quality threshold to obtain a second comparison result. Based on the first comparison result and the second comparison result, the first mass is updated to obtain the second mass of the vehicle.

3. The method according to claim 2, characterized in that, The step of updating the first mass based on the first comparison result and the second comparison result to obtain the second mass of the vehicle includes: In response to the first comparison result indicating that the first reference quality is greater than the first quality, and the second comparison result indicating that the difference is greater than the quality threshold, the sum of the first reference quality and the quality threshold is determined as the second quality; In response to the first comparison result indicating that the first reference quality is greater than the first quality, and the second comparison result indicating that the difference is less than the quality threshold, the first reference quality is determined as the second quality; In response to the first comparison result indicating that the first reference quality is less than the first quality, and the second comparison result indicating that the difference is greater than the quality threshold, the first reference quality is subtracted from the quality threshold to obtain the second quality; In response to the first comparison result indicating that the first reference quality is less than the first quality, and the second comparison result indicating that the difference is less than the quality threshold, the first reference quality is determined as the second quality.

4. The method according to claim 1, characterized in that, The step of iteratively updating the second mass based on the second driving parameters at the second time moment to obtain the target mass of the vehicle includes: Based on the second driving parameters at the first second moment, the second mass is updated to obtain the first target mass of the vehicle; Iteration i performs the following processing: Based on the second driving parameters at the (i-1)th second time step, the (i-1)th target mass is updated to obtain the ith target mass. N is used to indicate the total number of the second time moments, where the i-th second time moment is later than the (i-1)-th second time moment; The target mass of the vehicle is determined based on the Nth target mass.

5. The method according to claim 4, characterized in that, The process of updating the target quality based on the second driving parameters at the (i-1)th second time moment to obtain the target quality includes: Based on the second driving parameters at the (i-1)th second time moment, the mass of the vehicle is estimated to obtain the second reference mass of the vehicle at the (i-1)th second time moment; The second reference quality is compared with the (i-1)th target quality to obtain a third comparison result, and the difference between the second reference quality and the (i-1)th target quality is compared with a quality threshold to obtain a fourth comparison result. Based on the third comparison result and the fourth comparison result, the (i-1)th target quality is updated to obtain the i-th target quality.

6. The method according to claim 4, characterized in that, Determining the target mass of the vehicle based on the Nth target mass includes: Based on the first target mass to the Nth target mass, determine the rate of mass change of the vehicle during the first N iterations of mass update; The mass change rate is compared with a change rate threshold to obtain a fifth comparison result, and the target mass of the vehicle is determined based on the fifth comparison result.

7. The method according to claim 6, characterized in that, Determining the target mass of the vehicle based on the fifth comparison result includes: In response to the fifth comparison result indicating that the rate of change of mass is less than the rate of change threshold, the target mass of the vehicle is determined as the Nth target mass; In response to the fifth comparison result indicating that the rate of change of mass is greater than or equal to the rate of change threshold, the Nth target mass is iteratively updated based on the third driving parameters of the vehicle at at least a third time, until the rate of change of mass of the vehicle after the second time is less than the rate of change threshold. The updated Nth target mass of the corresponding iteration round is determined as the target mass of the vehicle, wherein the third time is later than the second time.

8. A vehicle mass determination device, characterized in that, The device includes: The first detection module is used to obtain a preset first mass of the vehicle and to perform parameter detection on the vehicle at a first moment during the vehicle's driving process to obtain the first driving parameters of the vehicle at the first moment. The first update module is used to update the first mass based on the first driving parameters to obtain the second mass of the vehicle; The second detection module is used to perform parameter detection on the vehicle at multiple second moments during the vehicle's driving process, and obtain the second driving parameters of the vehicle at each second moment, wherein the second moment is later than the first moment; The second update module is used to iteratively update the second mass based on the second driving parameters at the second time moment to obtain the target mass of the vehicle.

9. An electronic device, characterized in that, The electronic device includes: Memory is used to store executable instructions or computer programs. A processor, when executing computer-executable instructions or computer programs stored in the memory, implements the vehicle mass determination method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing computer-executable instructions or a computer program, characterized in that, When the computer-executable instructions or computer program are executed by a processor, the method for determining the mass of a vehicle as described in any one of claims 1 to 7 is implemented.

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