Vehicle dynamics performance index setting method, system and device and medium
By acquiring evaluation scenario and key indicator information, and decomposing and determining vehicle dynamic performance indicators, the problem of insufficient multi-dimensional performance coverage in traditional methods is solved, and more accurate vehicle performance settings and testing results are achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-18
- Publication Date
- 2026-03-13
AI Technical Summary
Traditional methods for setting vehicle dynamics performance targets are insufficient to cover multi-dimensional performance, resulting in inaccurate vehicle performance results.
By acquiring evaluation scenario information and key indicator information, the pre-set target evaluation scenarios and key evaluation indicators are determined. The evaluation indicators and their weight information for each target evaluation scenario are decomposed and determined. The objective function is constructed using the least squares method, and the first target score of the common evaluation indicators is fitted to achieve comprehensive dynamic performance analysis.
This improved the coverage of vehicle dynamics performance indicators across different performance dimensions, enhancing the effectiveness of subsequent vehicle testing.
Smart Images
Figure CN121659445A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of vehicle testing and evaluation technology, and in particular to a method, system, device and medium for setting vehicle dynamic performance indicators. Background Technology
[0002] In related technologies, with the development of the automotive industry, users' requirements for vehicle dynamics performance are gradually increasing. Correspondingly, the accurate setting of vehicle dynamics performance targets during the vehicle development process is crucial to the final performance of the actual vehicle.
[0003] Although there are many objective indicators for dynamic performance, traditional target setting methods are generally based on a single objective indicator and a horizontal comparison with competitors. They may also take into account the performance positioning of the vehicle model when setting targets. This target setting method is difficult to cover multi-dimensional performance.
[0004] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the Invention
[0005] The main objective of this application is to propose a method, system, device, and medium for setting vehicle dynamics performance indicators, aiming to improve the coverage of the set vehicle dynamics performance indicators for different performance dimensions and improve the subsequent vehicle testing results around the performance indicators.
[0006] To achieve the above objectives, one aspect of this application proposes a method for setting vehicle dynamics performance indicators, the method comprising: Acquire evaluation scenario information and key indicator information, wherein the evaluation scenario information includes several preset target evaluation scenarios and the key indicator information includes several preset key evaluation indicators; Based on the target evaluation scenario, an evaluation indicator associated with each target evaluation scenario is determined, and the weight information of the evaluation indicator associated with each target evaluation scenario is determined respectively. The evaluation indicator includes the key evaluation indicator, and different target evaluation scenarios can be associated with the same evaluation indicator. For each target evaluation scenario, a first target score for different evaluation indicators is determined based on the evaluation scenario information, the key indicator information, and the weight information. The vehicle dynamics performance index is determined based on the first target score of the evaluation index.
[0007] In some embodiments, the evaluation scenario information further includes a second target score for the target evaluation scenario, and the key indicator information further includes a first target score for the key evaluation indicator. For each target evaluation scenario, determining the first target score for different evaluation indicators based on the evaluation scenario information, the key indicator information, and the weight information includes: For each target evaluation scenario, the first target score of the common evaluation index associated with the target evaluation scenario is determined based on the second target score of the corresponding target evaluation scenario, the first target score of the key evaluation index associated with the corresponding target evaluation scenario, and the weight information decomposition. The indexes other than the key evaluation indexes in the evaluation indexes are defined as the common evaluation indexes.
[0008] In some embodiments, determining the first target score of the common evaluation indicator associated with the corresponding target evaluation scenario based on the second target score of the corresponding target evaluation scenario, the first target score of the key evaluation indicator associated with the corresponding target evaluation scenario, and the weight information decomposition includes: Construct an objective function based on the least squares method; The objective function is used to determine the first objective score of the common evaluation index associated with the corresponding objective evaluation scenario based on the second objective score of the corresponding objective evaluation scenario, the first objective score of the key evaluation index associated with the corresponding objective evaluation scenario, and the weight information decomposition.
[0009] In some embodiments, constructing the objective function based on the least squares method includes: Obtain the lower boundary conditions for each of the evaluation indicators, wherein the lower boundary conditions are boundary conditions for the first target score; The objective function based on least squares is constructed according to the second objective score, the first objective score, the weight information, and the lower boundary condition.
[0010] In some embodiments, indicators other than the key evaluation indicators are defined as ordinary evaluation indicators. After determining the first target score of different evaluation indicators based on the evaluation scenario information, the key indicator information, and the weight information, the method further includes: In response to the fact that different target evaluation scenarios are associated with the same common evaluation index, the corresponding common evaluation index is defined as the target evaluation index, the target evaluation index is set as the key evaluation index, and the key index information is updated according to the first target score of the target evaluation index. Then, the process of determining the evaluation index associated with each target evaluation scenario according to the target evaluation scenario is returned, and the weight information of the evaluation index associated with each target evaluation scenario is determined respectively.
[0011] In some embodiments, the target evaluation indicator has different first target scores in different associated target evaluation scenarios, and updating the key indicator information based on the first target score of the target evaluation indicator includes: The key indicator information is updated based on the highest first target score in different target evaluation scenarios.
[0012] In some embodiments, determining the vehicle dynamics performance index based on the first target score of the evaluation index includes: The transformation function for each evaluation indicator is determined according to the data type of the evaluation indicator; The first target score of the evaluation index is converted into an index value using the conversion function, and the vehicle dynamics performance index is determined based on the index value.
[0013] To achieve the above objectives, another aspect of this application proposes a vehicle dynamics performance index setting system, the system comprising: The information preparation module is used to acquire evaluation scenario information and key indicator information. The evaluation scenario information includes several preset target evaluation scenarios, and the key indicator information includes several preset key evaluation indicators. The preprocessing module is used to determine the evaluation index associated with each target evaluation scenario based on the target evaluation scenario, and to determine the weight information of the evaluation index associated with each target evaluation scenario respectively, wherein the evaluation index includes the key evaluation index, and different target evaluation scenarios can be associated with the same evaluation index. The indicator score decomposition module is used to determine the first target score of different evaluation indicators for each target evaluation scenario based on the evaluation scenario information, the key indicator information and the weight information. The indicator confirmation module is used to determine the vehicle dynamics performance indicator based on the first target score of the evaluation indicator.
[0014] To achieve the above objectives, another aspect of this application provides a computer device including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method.
[0015] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.
[0016] The embodiments of this application include at least the following beneficial effects: This application provides a method, system, device, and medium for setting vehicle dynamics performance indicators. This solution obtains evaluation scenario information and key indicator information to determine pre-set target evaluation scenarios and key evaluation indicators. It then further determines the evaluation indicators for each target evaluation scenario, as well as the weight information of each evaluation indicator. For each target evaluation scenario, it decomposes and determines the first target score of different evaluation indicators based on the evaluation scenario information, key indicator information, and weight information. The requirements for each evaluation indicator are determined through the first target score, thereby determining the vehicle dynamics performance indicators based on the first target score. Compared to comparisons based on a single objective indicator, the method of this application can decompose and determine the first target score of other evaluation indicators based on preset target evaluation scenarios and key evaluation indicators. This allows for the analysis of key evaluation indicators while also extending to other evaluation indicators, enabling comprehensive dynamics performance analysis, improving the coverage of the set vehicle dynamics performance indicators across different performance dimensions, and enhancing the subsequent vehicle testing results related to performance indicators. Attached Figure Description
[0017] Figure 1 This is a flowchart of a method for setting vehicle dynamics performance indicators provided in an embodiment of this application; Figure 2 yes Figure 1 The flowchart of step S103 in the process; Figure 3 yes Figure 2 The flowchart of step S301 in the process; Figure 4 yes Figure 3 The flowchart of step S311 in the text; Figure 5 This is another flowchart of a method for setting vehicle dynamics performance indicators provided in an embodiment of this application; Figure 6 yes Figure 1 The flowchart of step S104 in the process; Figure 7 This is a schematic diagram of the vehicle dynamics performance index setting system provided in the embodiments of this application; Figure 8 This is a schematic diagram of the hardware structure of the computer device provided in the embodiments of this application. Detailed Implementation
[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.
[0019] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various concepts, but unless otherwise stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words “if,” “when,” or “in response to a determination” as used herein may be interpreted as “when…” or “when…” or “in response to a determination.”
[0020] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.
[0021] 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 herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.
[0022] In related technologies, with the development of the automotive industry, users' requirements for vehicle dynamics performance are gradually increasing. Correspondingly, the accurate setting of vehicle dynamics performance targets during the vehicle development process is crucial to the final performance of the actual vehicle.
[0023] Although there are many objective indicators for dynamic performance, traditional target setting methods are generally based on a single objective indicator and a horizontal comparison with competitors. They may also take into account the performance positioning of the vehicle model when setting targets. This target setting method is difficult to cover multi-dimensional performance.
[0024] In view of this, this application provides a method, system, device, and medium for setting vehicle dynamics performance indicators. This solution obtains evaluation scenario information and key indicator information to determine pre-set target evaluation scenarios and key evaluation indicators. It then further determines the evaluation indicators for each target evaluation scenario and the weight information of each evaluation indicator. For each target evaluation scenario, a first target score for each evaluation indicator is determined based on the evaluation scenario information, key indicator information, and weight information. The requirements for each evaluation indicator are determined based on the first target score, thereby determining the vehicle dynamics performance indicators. Compared to comparisons based on a single objective indicator, this method can decompose and determine the first target score for other evaluation indicators based on preset target evaluation scenarios and key evaluation indicators. This allows for the analysis of key evaluation indicators while also extending to other evaluation indicators, enabling comprehensive dynamics performance analysis. This improves the coverage of the set vehicle dynamics performance indicators across different performance dimensions and enhances the effectiveness of subsequent vehicle testing related to these performance indicators.
[0025] The vehicle dynamics performance index setting method provided in this application relates to the field of vehicle testing and evaluation technology. The vehicle dynamics performance index setting method provided in this application can be applied to a terminal, a server, or software running on a terminal or server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or in-vehicle terminal, but is not limited to these. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing the vehicle dynamics performance index setting method, but is not limited to the above forms.
[0026] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.
[0027] Figure 1 This is an optional flowchart of the vehicle dynamics performance index setting method provided in the embodiments of this application. Figure 1 The method may include, but is not limited to, steps S101 to S104.
[0028] Step S101: Obtain evaluation scenario information and key indicator information. The evaluation scenario information includes several preset target evaluation scenarios, and the key indicator information includes several preset key evaluation indicators.
[0029] When setting vehicle dynamics performance indicators, based on the performance positioning of different vehicle models, some scenarios and some indicators are items that must be evaluated, and hard performance requirements are also set for them. These types of scenarios and indicators are defined as the target evaluation scenario and the key evaluation indicator, respectively. For example, the target evaluation scenario may include scenarios such as driving on mountain roads, driving on urban roads, and driving over speed bumps, while the key evaluation indicator may include indicators such as roll gradient, yaw rate overshoot, and peak-to-peak vertical acceleration.
[0030] It should be noted that although both the target assessment scenario and the key assessment indicators are pre-defined, there is currently no correlation between the two. They are determined based on the assessment scenario information and the key indicator information, respectively.
[0031] Step S102: Determine the evaluation indicators associated with each target evaluation scenario based on the target evaluation scenario, and determine the weight information of the evaluation indicators associated with each target evaluation scenario. The evaluation indicators include key evaluation indicators, and different target evaluation scenarios can be associated with the same evaluation indicator.
[0032] In addition to the key evaluation indicators mentioned above, other evaluation indicators need to be added to improve the coverage of the set vehicle dynamics performance indicators across different performance dimensions. Therefore, based on the evaluation requirements of the target evaluation scenarios, the evaluation indicators associated with each target evaluation scenario are determined. These scenario requirements can be set separately for each scenario based on the designer's experience, thereby determining the evaluation indicators associated with each scenario. Different target evaluation scenarios may have evaluation requirements for the same evaluation indicators; for example, both mountain road driving and urban road driving require evaluation of roll gradient.
[0033] Key performance indicators (KPIs) are a subset of evaluation metrics. For any target evaluation scenario, key performance indicators may or may not be present among the associated evaluation metrics, and multiple key performance indicators may exist. For clarity, metrics other than key performance indicators are defined as ordinary evaluation metrics. The difference between key and ordinary evaluation metrics is that the relevant information for key performance indicators can be directly confirmed from the key indicator information, and the known performance requirements are explicit. Ordinary evaluation metrics, on the other hand, require processing in subsequent steps to obtain the information. After determining the evaluation metrics associated with each scenario, we can first determine the key performance indicators included in the evaluation metrics associated with each scenario.
[0034] Furthermore, different target evaluation scenarios are assigned weights to their associated evaluation indicators, and the weight of each evaluation indicator is defined as the weight information. The weight allocation rules can be set based on the designer's experience, or the importance of each evaluation indicator can be determined through the analytic hierarchy process (AHP), and then weights can be assigned according to their importance. Whether an indicator is a key evaluation indicator is irrelevant to its weight, and since weights are assigned separately for different target evaluation scenarios, the same evaluation indicator may be assigned different weights in different target evaluation scenarios. For example, the weight allocation can be shown in Table 1 below.
[0035] Table 1 Evaluation indicators and weight allocation for target evaluation scenarios
[0036] Step S103: For each target evaluation scenario, the first target score of different evaluation indicators is determined based on the evaluation scenario information, key indicator information and weight information.
[0037] Based on the weight information in Table 1 above, and combined with the performance requirements of different key evaluation indicators in the evaluation scenario information and key indicator information, as well as the comprehensive performance requirements of different target evaluation scenarios, the requirements are decomposed. As explained above, the difference between key evaluation indicators and ordinary evaluation indicators is that ordinary evaluation indicators do not specify performance requirements. The purpose of this decomposition operation is to determine the performance requirements of each ordinary evaluation indicator.
[0038] refer to Figure 2 In some embodiments, step S103 includes: Step S301: For each target evaluation scenario, determine the first target score of the common evaluation index associated with the corresponding target evaluation scenario based on the second target score of the corresponding target evaluation scenario, the first target score of the key evaluation index associated with the corresponding target evaluation scenario, and the weight information decomposition.
[0039] Optionally, the comprehensive performance requirements of the target evaluation scenario and the performance requirements of the evaluation indicators (including key evaluation indicators) can be quantified in the form of scores. The scores of the evaluation indicators are defined as the first target score, and the scores of the target evaluation scenario are defined as the second target score. During subsequent performance testing, the test score must be greater than or equal to the first or second target score to be considered as meeting the comprehensive performance requirements of the corresponding target evaluation scenario or the performance requirements of the corresponding evaluation indicator. Furthermore, since the requirements of the target evaluation scenario and key evaluation indicators are pre-specified, the second target score of the target evaluation scenario can be directly determined based on the evaluation scenario information, and the first target score of the key evaluation indicator can be directly determined based on the key indicator information.
[0040] Based on this, the second target score of the target evaluation scenario is known, the weight information of each associated evaluation indicator is known, and the first target score of the key evaluation indicator among the evaluation indicators is known. Using this information, a target decomposition operation can be performed to calculate the first target score of the appropriate ordinary evaluation indicator, thereby confirming the first target score of all evaluation indicators. The first target score and weight information of the ordinary evaluation indicators and key evaluation indicators should meet the requirements of the second target score; for example, as shown in Table 2 below, the roll gradient is a key evaluation indicator, and its first target score of 95 can be directly confirmed based on the key indicator information, while the first target scores of the yaw gain, maximum lateral adhesion, and steering sensitivity, which belong to the ordinary evaluation indicators, are calculated according to the target decomposition operation in this embodiment.
[0041] Table 2. Scores of Target Assessment Scenarios and Related Assessment Indicators
[0042] By determining the first target score of common evaluation indicators through target decomposition, the performance indicators can be extended from the set key evaluation indicators to other common evaluation indicators. This also takes into account the evaluation requirements of the target evaluation scenario, thereby improving the coverage of performance indicators across different dimensions of performance.
[0043] refer to Figure 3 In some embodiments, step S301 includes: Step S311: For each target evaluation scenario, construct an objective function based on the least squares method.
[0044] Step S312: Using the objective function, determine the first target score of the common evaluation index associated with the corresponding target evaluation scenario based on the second target score of the corresponding target evaluation scenario, the first target score of the key evaluation index associated with the corresponding target evaluation scenario, and the weight information decomposition.
[0045] Optionally, the objective decomposition operation can be combined with the least squares method, which is a method for achieving the best fit to experimental data in the sense of variance, generally making the fitting function... The goal is to minimize the sum of squares of the deviations between the values at the given location and the experimental values. In this embodiment, a target function based on the least squares method is constructed based on the aforementioned known information, and the first target score of the common evaluation index is calculated using this target function.
[0046] By applying the least squares method to fit the first target score of a common evaluation index, the accuracy of the first target score is improved, thereby enhancing the performance of subsequent vehicle tests related to performance indicators.
[0047] refer to Figure 4 In some embodiments, step S311 includes: Step S321: Obtain the lower boundary conditions for each evaluation index. The lower boundary conditions are the boundary conditions for the first target score.
[0048] Step S322: Construct an objective function based on the least squares method according to the second objective score, the first objective score, weight information and lower boundary conditions.
[0049] The objective function constructed based on the least squares method includes two constraints: the first is the difference between the score of each evaluation index calculated based on the weight parameters and the first target score and the second target score; the second is the difference between the assumed score of a common evaluation index and its lower boundary condition. The lower boundary condition is the lower limit boundary condition for the first target score. Taking the evaluation index lateral gradient as an example, there is an upper boundary condition of 100 and a lower boundary condition of 85. As a key evaluation index, the lateral gradient's first target score is preset to 95, which normally falls within the range of the upper and lower boundary conditions. For common evaluation indices with unknown first target scores, at least the lower boundary condition must be met to achieve the performance requirements. Regarding the upper boundary condition, since higher scores generally indicate better performance for evaluation indices, but also increase costs, this embodiment only includes the lower boundary condition in the function for calculation. In other embodiments, the upper boundary condition can be added as a third constraint.
[0050] Specifically, refer to the following formulas (1) and (2): (1) (2) in, The objective function value, This is the second objective score for the corresponding objective evaluation scenario. To calculate the scores for each evaluation indicator based on the weighting parameters and the first target score, These are the weighting parameters for common evaluation indicators. The weighting parameters for key evaluation indicators, Let x be the first target score of the key evaluation indicator, x be the assumed score of the ordinary evaluation indicator, and LB be the score corresponding to the lower boundary condition. Through the above equations (1) and (2), the most matching assumed score of the ordinary evaluation indicator can be obtained by fitting, and this assumed score is determined as the first target score.
[0051] By constructing an objective function based on the least squares method under the above two constraints, the first target score of the common evaluation index is obtained through fitting. This ensures that the common evaluation index can meet the performance requirements while improving the accuracy of its first target score, thereby improving the subsequent vehicle testing results around the performance index.
[0052] refer to Figure 5 In some embodiments, after step S103, the following steps are also included: Step S302: In response to the fact that different target evaluation scenarios are associated with the same common evaluation indicators, define the corresponding common evaluation indicators as target evaluation indicators, set the target evaluation indicators as key evaluation indicators, update the key indicator information according to the first target score of the target evaluation indicators, and return to the execution step S102.
[0053] In the method of this application, since different target evaluation scenarios can be associated with the same common evaluation index, such as the mountain road driving and urban road driving scenarios in Table 1, both are associated with the common evaluation index steering sensitivity. In step S103, since different target evaluation scenarios will determine the first target score of their associated common evaluation index, the common evaluation index may determine two or more different first target scores (corresponding to different target evaluation scenarios). For example, the first target score of steering sensitivity obtained by fitting in the mountain road driving scenario is 92, while the first target score of steering sensitivity obtained by fitting in the urban road driving scenario is 96.
[0054] For ease of explanation, the common evaluation index is defined as the target evaluation index. If the target evaluation index has two or more first target scores, it will be difficult to determine the true requirements of this index in subsequent step S104. Since the possible first target scores have already been determined through decomposition calculation, a truly matching value can be selected from these first target scores through a target reconstruction operation. Then, the first target score of the target evaluation index is pre-specified based on this value, avoiding the need to calculate two or more values in step 103. At the same time, this is equivalent to treating the target evaluation index as a key evaluation index (also pre-specifying its first target score). Based on this, the key index information is updated according to the target evaluation index and its first target score. The target evaluation index is added to the key evaluation index, and its first target score is specified. Steps S102 and S103 are re-executed with the target evaluation index as the key evaluation index, thereby updating the first target scores of other common evaluation indicators.
[0055] In addition, if the common evaluation indicators associated with different target evaluation scenarios are not the same, step S104 can be executed directly.
[0056] By resetting key evaluation indicators based on target evaluation indicators and returning to execution step S102, it is ensured that these target evaluation indicators have only a unique first target score, clarifying the performance requirements of the corresponding indicators and improving the accuracy of performance indicators.
[0057] In step S302 of some embodiments, updating the key indicator information according to the first target score of the target evaluation indicator includes: The key indicator information is updated based on the highest first target score in different target evaluation scenarios.
[0058] Because higher scores correlate with better performance, the largest possible score among the first target scores for the evaluation metric represents the scenario with the highest performance requirement. Simultaneously, the largest score will also necessarily meet the requirements of the second target scores for other evaluation scenarios. Therefore, the largest first target score for this evaluation metric is selected as its pre-designated first target score, and the key indicator information is updated accordingly to ensure that the final determined performance indicators meet the comprehensive performance requirements of each evaluation scenario.
[0059] Step S104: Determine the vehicle dynamics performance index based on the first target score of the evaluation index.
[0060] After determining the first target score for each evaluation indicator, these evaluation indicators and their first target scores can be extracted from the target evaluation scenario. The first target score represents the performance requirement of the corresponding indicator and can be used to further determine the actual vehicle dynamics performance indicators.
[0061] refer to Figure 6 In some embodiments, step S104 includes: Step S401: Determine the transformation function for each evaluation indicator based on the data type of the evaluation indicator.
[0062] Step S402: The first target score of the evaluation index is converted into an index value through a conversion function, and the vehicle dynamic performance index is determined based on the index value.
[0063] For different evaluation indicators, due to their different data types, the conversion relationship between the first target score and the actual indicator value exists differently. For example, compared to yaw gain, the indicator value corresponding to each point of the first target score cannot be the same, and the dimensions of the indicator values are completely different. Correspondingly, in this embodiment, a conversion function is set up for the conversion between the first target score and the indicator value according to the data type of each evaluation indicator. For any evaluation indicator, the corresponding conversion function is selected according to the data type of the evaluation indicator, and then the first target score is input into the conversion function. The first target score can be converted into the corresponding indicator value through the conversion function, thereby confirming the actual indicator value requirement of the evaluation indicator. For example, refer to Table 3 below.
[0064] Table 3. Correspondence between the first target score and the indicator value of the evaluation indicators
[0065] By converting the first target score of each evaluation indicator into an indicator value through a transformation function, the specific indicator value requirements are determined, thereby obtaining vehicle dynamics performance indicators that cover multiple dimensions of performance indicators.
[0066] Steps S101 to S104 as shown in the embodiments of this application decompose and determine the first target score of other evaluation indicators based on the preset target evaluation scenario and key evaluation indicators. In this way, while analyzing the key evaluation indicators, it can also extend to other evaluation indicators, conduct comprehensive dynamic performance analysis, improve the coverage of the set vehicle dynamic performance indicators for different dimensions of performance, and improve the subsequent vehicle testing effect around the performance indicators.
[0067] The following is a detailed description and explanation of the solutions in the embodiments of the present invention, using specific application examples: In this embodiment of the application, a method for setting vehicle dynamics performance indicators is provided. This method can be applied to the vehicle production design stage to assist in performance testing and evaluation after actual vehicle production.
[0068] The assessment scenario information and key indicator information are obtained. The assessment scenario information includes several preset target assessment scenarios and a second target score for each target assessment scenario. The key indicator information includes several preset key assessment indicators and a first target score for each key assessment indicator.
[0069] Based on the target evaluation scenario, determine the evaluation indicators associated with each target evaluation scenario, and determine the weight information of the evaluation indicators associated with each target evaluation scenario. The evaluation indicators include key evaluation indicators, and different target evaluation scenarios can be associated with the same evaluation indicator.
[0070] For each target evaluation scenario, the lower boundary conditions of each evaluation indicator are obtained. These lower boundary conditions are boundary conditions for the first target score. A least-squares-based objective function is constructed based on the second target score, the first target score, weight information, and the lower boundary conditions. Using this objective function, the first target score of the common evaluation indicator associated with the corresponding target evaluation scenario is determined based on the second target score of the corresponding target evaluation scenario, the first target score of the key evaluation indicator associated with the corresponding target evaluation scenario, and the weight information. Then, it is determined whether different target evaluation scenarios are associated with the same common evaluation indicator. If so, the corresponding common evaluation indicator is defined as the target evaluation indicator, set as the key evaluation indicator, and the key indicator information is updated based on the largest first target score of the target evaluation indicator in different target evaluation scenarios. The process then returns to the previous steps of determining the evaluation indicators associated with each target evaluation scenario and determining the weight information of the evaluation indicators associated with each target evaluation scenario.
[0071] Then, based on the data type of the evaluation index, the transformation function of each evaluation index is determined; through the transformation function, the first target score of the evaluation index is converted into an index value, and the vehicle dynamic performance index is determined based on the index value.
[0072] This application embodiment, based on a preset target evaluation scenario and key evaluation indicators, decomposes and determines the first target score of other evaluation indicators. Thus, while analyzing the key evaluation indicators, it can also extend to other evaluation indicators, conduct comprehensive dynamic performance analysis, improve the coverage of the set vehicle dynamic performance indicators for different dimensions of performance, and improve the subsequent vehicle testing effect around the performance indicators.
[0073] Please see Figure 7 This application also provides a vehicle dynamics performance index setting system that can implement the above method. The system includes: The information preparation module is used to obtain evaluation scenario information and key indicator information. The evaluation scenario information includes several preset target evaluation scenarios, and the key indicator information includes several preset key evaluation indicators.
[0074] The preprocessing module is used to determine the evaluation indicators associated with each target evaluation scenario based on the target evaluation scenario, and to determine the weight information of the evaluation indicators associated with each target evaluation scenario. The evaluation indicators include key evaluation indicators, and different target evaluation scenarios can be associated with the same evaluation indicator.
[0075] The indicator score decomposition module is used to determine the first target score of different evaluation indicators for each target evaluation scenario based on the evaluation scenario information, key indicator information, and weight information.
[0076] The indicator confirmation module is used to determine the vehicle dynamics performance indicators based on the first target score of the evaluation indicators.
[0077] It is understood that the content of the above method embodiments is applicable to this system embodiment. The specific functions implemented in this system embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.
[0078] This application also provides a computer device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This computer device can be any smart terminal, including tablet computers, in-vehicle computers, etc.
[0079] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.
[0080] Please see Figure 8 , Figure 8 The hardware structure of a computer device according to another embodiment is illustrated. The computer device includes: The processor 801 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 802 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 802 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 802 and is called and executed by the processor 801 using the methods described in the embodiments of this application. The 803 input / output interface is used to implement information input and output. The communication interface 804 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 805 transmits information between various components of the device (e.g., processor 801, memory 802, input / output interface 803, and communication interface 804); The processor 801, memory 802, input / output interface 803, and communication interface 804 are connected to each other within the device via bus 805.
[0081] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.
[0082] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.
[0083] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.
[0084] The vehicle dynamics performance index setting method, system, device, and medium provided in this application embodiment obtain evaluation scenario information and key index information to determine pre-set target evaluation scenarios and key evaluation indicators. Then, it further determines the evaluation indicators for each target evaluation scenario and the weight information of each evaluation indicator. For each target evaluation scenario, it decomposes and determines the first target score of different evaluation indicators based on the evaluation scenario information, key index information, and weight information. The requirements for each evaluation indicator are determined by the first target score, thereby determining the vehicle dynamics performance index based on the first target score. Compared with comparisons based on a single objective indicator, the method of this application can decompose and determine the first target score of other evaluation indicators based on preset target evaluation scenarios and key evaluation indicators. This allows for the analysis of key evaluation indicators while also extending to other evaluation indicators, enabling comprehensive dynamics performance analysis, improving the coverage of the set vehicle dynamics performance indicators across different performance dimensions, and enhancing the effectiveness of subsequent vehicle testing related to performance indicators.
[0085] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.
[0086] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.
[0087] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.
[0088] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.
[0089] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0090] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.
[0091] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.
[0092] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0093] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.
[0094] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0095] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.
Claims
1. A method for setting vehicle dynamics performance indicators, characterized in that, The method includes the following steps: Acquire evaluation scenario information and key indicator information, wherein the evaluation scenario information includes several preset target evaluation scenarios and the key indicator information includes several preset key evaluation indicators. Based on the target evaluation scenario, an evaluation indicator associated with each target evaluation scenario is determined, and the weight information of the evaluation indicator associated with each target evaluation scenario is determined respectively. The evaluation indicator includes the key evaluation indicator, and different target evaluation scenarios can be associated with the same evaluation indicator. For each target evaluation scenario, a first target score for different evaluation indicators is determined based on the evaluation scenario information, the key indicator information, and the weight information. The vehicle dynamics performance index is determined based on the first target score of the evaluation index.
2. The method according to claim 1, characterized in that, The evaluation scenario information also includes a second target score for the target evaluation scenario, and the key indicator information also includes a first target score for the key evaluation indicator. For each target evaluation scenario, determining the first target score for different evaluation indicators based on the evaluation scenario information, the key indicator information, and the weight information includes: For each target evaluation scenario, the first target score of the common evaluation index associated with the target evaluation scenario is determined based on the second target score of the corresponding target evaluation scenario, the first target score of the key evaluation index associated with the corresponding target evaluation scenario, and the weight information decomposition. The indexes other than the key evaluation indexes in the evaluation indexes are defined as the common evaluation indexes.
3. The method according to claim 2, characterized in that, The step of determining the first target score of the common evaluation indicator associated with the corresponding target evaluation scenario based on the second target score of the corresponding target evaluation scenario, the first target score of the key evaluation indicator associated with the corresponding target evaluation scenario, and the weight information decomposition includes: Construct an objective function based on the least squares method; The objective function is used to determine the first objective score of the common evaluation index associated with the corresponding objective evaluation scenario based on the second objective score of the corresponding objective evaluation scenario, the first objective score of the key evaluation index associated with the corresponding objective evaluation scenario, and the weight information decomposition.
4. The method according to claim 3, characterized in that, The construction of the objective function based on the least squares method includes: Obtain the lower boundary conditions for each of the evaluation indicators, wherein the lower boundary conditions are boundary conditions for the first target score; The objective function based on least squares is constructed according to the second objective score, the first objective score, the weight information, and the lower boundary condition.
5. The method according to claim 1, characterized in that, The evaluation indicators other than the key evaluation indicators are defined as ordinary evaluation indicators. After determining the first target score of different evaluation indicators based on the evaluation scenario information, the key indicator information, and the weight information, the method further includes: In response to the fact that different target evaluation scenarios are associated with the same common evaluation index, the corresponding common evaluation index is defined as the target evaluation index, the target evaluation index is set as the key evaluation index, and the key index information is updated according to the first target score of the target evaluation index. Then, the process of determining the evaluation index associated with each target evaluation scenario according to the target evaluation scenario is returned, and the weight information of the evaluation index associated with each target evaluation scenario is determined respectively.
6. The method according to claim 5, characterized in that, The target evaluation indicator has different first target scores in different associated target evaluation scenarios. Updating the key indicator information based on the first target score of the target evaluation indicator includes: The key indicator information is updated based on the highest first target score in different target evaluation scenarios.
7. The method according to any one of claims 1 to 6, characterized in that, The step of determining the vehicle dynamics performance index based on the first target score of the evaluation index includes: The transformation function for each evaluation indicator is determined according to the data type of the evaluation indicator; The first target score of the evaluation index is converted into an index value using the conversion function, and the vehicle dynamics performance index is determined based on the index value.
8. A vehicle dynamics performance index setting system, characterized in that, The system includes: The information preparation module is used to acquire evaluation scenario information and key indicator information. The evaluation scenario information includes several preset target evaluation scenarios, and the key indicator information includes several preset key evaluation indicators. The preprocessing module is used to determine the evaluation index associated with each target evaluation scenario based on the target evaluation scenario, and to determine the weight information of the evaluation index associated with each target evaluation scenario respectively, wherein the evaluation index includes the key evaluation index, and different target evaluation scenarios can be associated with the same evaluation index. The indicator score decomposition module is used to determine the first target score of different evaluation indicators for each target evaluation scenario based on the evaluation scenario information, the key indicator information and the weight information. The indicator confirmation module is used to determine the vehicle dynamics performance indicator based on the first target score of the evaluation indicator.
9. A computer device, characterized in that, The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.