Selection and testing methods, devices, electronic equipment and storage media for automotive-grade chips
By establishing a automotive-grade chip database and obtaining real-time working data of the automotive controller, dynamically adjusting the proportion of working parameters selection, selecting and testing chips, the problems of inefficiency and poor adaptability of traditional selection and testing methods are solved, and efficient and accurate chip selection and testing are achieved.
Patent Information
- Application Number
- CN202411658848.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-19
- Publication Date
- 2025-04-08
AI Technical Summary
The traditional automotive-grade chip selection test method is inefficient, has fixed parameters, and poor adaptability, resulting in inconsistent selection results and is unable to adapt to the needs changes of different models and application scenarios.
By establishing a automotive-grade chip database, real-time working data and working parameter requirements of the automotive controller, determining the work scenario, key parameters and working range, dynamically adjusting the selection ratio of working parameters, so as to select chips that meet the requirements from the database and test them to determine the target chip.
It improves the efficiency and accuracy of chip selection, reduces manual intervention, can adapt to the needs changes of different models and application scenarios, and reduces the chip test cycle and cost.
Smart Images
Figure CN119780662A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of chip selection and testing technology, and specifically to a selection and testing method, device, electronic equipment and storage medium for an automotive-grade chip. Background Art
[0002] With the continuous development of automotive electronic technology, automotive-grade chips are being used more and more widely in the automotive industry. The selection and test recommendation of automotive-grade chips is a key link in ensuring the reliability and safety of automotive electronic products. At present, the selection and test of automotive-grade chips is mainly based on the chip selection and test method based on manual experience and fixed parameters. This method requires manually screening out potential chip models according to the needs of the automotive controller by consulting the information and data manuals provided by the chip manufacturer. Subsequently, these screened chip models are subjected to a series of standard tests to verify their performance. This method has the following disadvantages: 1. Low efficiency of manual selection: The traditional method relies on the experience of engineers to select chips, which is labor-intensive, time-consuming, and prone to inconsistent selection results due to differences in personal experience.
[0003] 2. Fixed parameters and poor adaptability: The parameter settings of traditional solutions are relatively fixed, making it difficult to adapt to changing needs of different vehicle models and application scenarios. Summary of the invention
[0004] In view of this, the present application provides a selection and testing method, device, electronic device and storage medium for automotive-grade chips to solve the problems of low efficiency, fixed parameters and poor adaptability of manual selection in traditional methods.
[0005] In a first aspect, an embodiment of the present application provides a method for selecting and testing an automotive-grade chip, the method comprising: Establish a database of automotive-grade chips; Obtain real-time working data and working parameter requirements of the vehicle controller; Determining a working scenario, key parameters, and a working range of key parameters of the vehicle controller according to real-time working data of the vehicle controller; Determining the selection weight of the working parameters of the automobile controller according to the working scenario of the automobile controller; According to the working parameter requirements, key parameters, working ranges of key parameters and selection weights of the working parameters of the automobile controller, a chip that meets the requirements is determined from the automotive-grade chip database; The chips meeting the requirements are tested to obtain target chips.
[0006] In a possible implementation, determining the working scene of the automobile controller according to the real-time working data of the automobile controller includes: Inputting the real-time working data of the automobile controller into a first data model; A working scenario of the automobile controller is determined according to an output result of the first data model.
[0007] In a possible implementation, determining the key parameters and key parameter operating ranges of the automobile controller according to the real-time operating data of the automobile controller includes: Extracting features of the real-time working data of the automobile controller to obtain data features of the real-time working data; The key parameters and the key parameter working ranges of the automobile controller are determined according to the data characteristics of the real-time working data.
[0008] In a possible implementation, determining the selection weight of the working parameters of the automobile controller according to the working scenario of the automobile controller includes: Determining the initial selection weight of the operating parameters of the vehicle controller; According to the working scenario of the automobile controller, the initial selection weight of the working parameters of the automobile controller is adjusted based on preset rules to obtain the selection weight of the working parameters of the automobile controller.
[0009] In a possible implementation, the weight of the selection of the working parameters is determined from the automotive-grade chip database to determine a chip that meets the requirements, including: Adjusting the working parameter requirements of the automobile controller according to the key parameters, the working range of the key parameters and the selection weight of the working parameters to obtain a target range of the working parameters of the automobile controller; Obtain chips whose working parameter range in the automotive-grade chip database and the target range of the working parameters of the automotive controller have a matching error within a preset range.
[0010] In a possible implementation, the chip that meets the requirements is tested to obtain a target chip: Determining test requirements for the chip based on target ranges of operating parameters of the automotive controller and historical operating data; Generating a test case for the chip according to specification parameters and failure modes of the chip; Testing the chip according to the test requirements of the chip and the test cases of the chip to obtain a test result; A target chip is determined from the chips meeting the requirements according to the test result.
[0011] In a possible implementation, testing the chip according to the test requirements of the chip and the test cases of the chip to obtain the test results includes: Testing the chip according to the test case of the chip to obtain a test result; Determining whether the test result meets the test requirements of the chip; When the test results of all chips do not meet the test requirements of the chip, iteratively optimize the test cases of the chip according to the test results until the test result of a certain chip meets the test requirements of the chip, and output the final test result; Determining a target chip from the chips meeting the requirements according to the test result includes: A target chip is determined from the chips that meet the requirements according to the final test result.
[0012] In a possible implementation, testing the chip according to the test requirements of the chip and the test cases of the chip to obtain the test results includes: Testing the chip according to the test case of the chip to obtain a test result; Determining whether the test result meets the test requirements of the chip; When the test results of at least two chips meet the test requirements of the chip, iteratively optimize the test cases of the chip according to the test results until the test result of only one chip meets the test requirements of the chip, and output the final test result; Determining a target chip from the chips meeting the requirements according to the test result includes: A target chip is determined from the chips that meet the requirements according to the final test result.
[0013] In a possible implementation, the iterative optimization of the test cases of the chip according to the test results includes: looping through the following steps: Analyzing the test results to identify failure modes and limit conditions in the test results; Optimizing test cases for the chip based on failure modes and extreme conditions in the test results; The chip is tested using the optimized test case of the chip to obtain a test result.
[0014] In a second aspect, an embodiment of the present application provides a device for selecting an automotive-grade chip, including: Establish a unit for establishing a database of automotive-grade chips; An acquisition unit, used to acquire real-time working data and working parameter requirements of the automobile controller; A first determining unit, configured to determine a working scenario, key parameters, and a working range of the key parameters of the vehicle controller according to real-time working data of the vehicle controller; A second determining unit, configured to determine a selection weight of working parameters of the automobile controller according to a working scenario of the automobile controller; A third determining unit is used to determine a chip that meets the requirements from the automotive-grade chip database according to the working parameter requirements, key parameters, working ranges of the key parameters and the selection weights of the working parameters of the automotive controller; The testing unit is used to test the chip that meets the requirements to obtain a target chip.
[0015] In a third aspect, an embodiment of the present application provides an electronic device, including: processor; Memory; A computer program is stored in the memory, and when the computer program is executed, the electronic device executes any one of the methods described in the first aspect.
[0016] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute any method described in the first aspect.
[0017] The embodiment of the present application can select chips according to the real-time working data and working parameter requirements of the automobile controller, and test the selected chips, which can adapt to the needs of different vehicle models and application scenarios, reduce manual intervention, and improve selection efficiency and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS
[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.
[0019] Figure 1 A schematic diagram of a flow chart of a method for selecting and testing an automotive-grade chip provided in an embodiment of the present application; Figure 2 A schematic diagram of a process for testing a chip provided in an embodiment of the present application; Figure 3 A schematic diagram of the structure of a vehicle-level control chip selection and testing device provided in an embodiment of the present application; Figure 4A schematic diagram of the structure of a test unit provided in an embodiment of the present application; Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0020] In order to better understand the technical solution of the present application, the embodiments of the present application are described in detail below with reference to the accompanying drawings.
[0021] It should be clear that the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.
[0022] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.
[0023] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.
[0024] With the continuous development of automotive electronic technology, automotive-grade chips are being used more and more widely in the automotive industry. The selection and test recommendation of automotive-grade chips is a key link in ensuring the reliability and safety of automotive electronic products. At present, the selection and test of automotive-grade chips is mainly based on the chip selection and test method based on manual experience and fixed parameters. This method requires manually screening out potential chip models according to the needs of the automotive controller by consulting the information and data manuals provided by the chip manufacturer. Subsequently, these screened chip models are subjected to a series of standard tests to verify their performance. This method has the following disadvantages: 1. Low efficiency of manual selection: The traditional method relies on the experience of engineers to select chips, which is labor-intensive, time-consuming, and prone to inconsistent selection results due to differences in personal experience.
[0025] 2. Fixed parameters and poor adaptability: The parameter settings of traditional solutions are relatively fixed, which makes it difficult to adapt to the changing needs of different models and application scenarios; 3. Incomplete testing: Traditional solutions for chip testing often only focus on some performance indicators, cannot fully evaluate the performance of the chip in actual applications, and cannot optimize for different chip characteristics.
[0026] 4. The analysis and feedback mechanism of test results is imperfect, resulting in long optimization cycles and high costs.
[0027] In response to the above problems, the embodiments of the present application provide a method, device, electronic device and storage medium for selecting and testing automotive-grade chips. The embodiments of the present application can select chips based on the real-time working data and working parameter requirements of the automobile controller, and test the selected chips, which can meet the needs of different vehicle models and application scenarios, reduce manual intervention, and improve the selection efficiency and accuracy. At the same time, the embodiments of the present application can also test the selected chips based on the actual working parameter requirements, and provide feedback optimization for the test cases, which improves the comprehensiveness of chip testing, reduces the chip testing cycle, and reduces the chip testing cost.
[0028] A detailed description is given below with reference to the accompanying drawings.
[0029] See also Figure 1 , is a flow chart of a method for selecting and testing a vehicle-grade chip provided in an embodiment of the present application. Figure 1 As shown, the specific steps include the following steps.
[0030] S101: Establish an automotive-grade chip database.
[0031] In one possible implementation, the specification parameters of various automotive-grade chips, such as operating voltage, temperature range, extreme operating conditions, etc., can be collected by referring to the information and data sheets provided by chip manufacturers, and then an automotive-grade chip database can be established based on the specification parameters of the automotive-grade chips.
[0032] S102: Acquire real-time working data and working parameter requirements of the vehicle controller; In one possible implementation, the vehicle information system can collect real-time working data of the vehicle controller, including voltage, temperature, load, etc., and send the data to the big data cloud platform. Specifically, the vehicle controller can send real-time working data to the vehicle information system through buses such as CAN / LIN / Ethernet, and the vehicle information system can establish a connection with the cloud platform through communication modules such as 4G / 5G / Wi-Fi, transmit the data to the cloud platform, and store it in the database.
[0033] In a possible implementation, the operating parameter requirements of the automobile controller can be obtained by referring to the operating manual of the automobile controller and the materials provided by the supplier of the automobile controller. Exemplarily, the operating parameter requirements of the automobile controller include standard operating ranges of parameters such as operating voltage, operating temperature, load and electromagnetic compatibility requirements.
[0034] S103: Determine a working scenario, key parameters, and working range of the key parameters of the vehicle controller according to the real-time working data of the vehicle controller.
[0035] In an embodiment of the present application, after obtaining the real-time working data of the automobile controller, the working scene of the automobile controller can be determined according to the real-time working data of the automobile controller, and the key parameters and key parameter working ranges of the automobile controller can be determined according to the real-time working data of the automobile controller.
[0036] In a possible implementation, the working scenario of the vehicle controller is determined based on the real-time working data of the vehicle controller, specifically including: inputting the real-time working data of the vehicle controller into a first data model, and determining the working scenario of the vehicle controller based on an output result of the first data model.
[0037] Specifically, the first data model may be a support vector machine (SVM). SVM is a supervised learning model widely used in classification and regression analysis. In the scene recognition of the embodiment of the present application, the first data model that can be used to distinguish the working scenes of different automobile controllers can be obtained by training the SVM. In a specific implementation, the SVM can be trained in the following manner: Data collection: Collect a large amount of historical working data of the vehicle controller, including the working voltage, working temperature, load and other parameters of the vehicle controller, as well as the corresponding working scene labels; Feature extraction: Extract features such as mean, standard deviation, maximum, minimum, etc. from the historical working data of the vehicle controller to characterize the characteristics of different scenarios; Data preprocessing: standardize or normalize the extracted feature data to facilitate SVM processing; Model training: Use the training data set obtained after standardization or normalization to train the SVM model, and select a suitable kernel function, such as a linear kernel, a polynomial kernel, a radial basis function kernel, etc., to obtain the first data model.
[0038] Model Validation: Use the validation dataset to evaluate the accuracy of the first data model and perform parameter tuning.
[0039] Model deployment: Deploy the trained first data model to the actual system for real-time scene recognition of the vehicle controller.
[0040] The embodiment of the present application uses a first data model to identify the working scene of the automobile controller according to the real-time working data of the automobile controller, thereby avoiding errors in manual identification of models based on experience, reducing personnel workload, and improving the efficiency and accuracy of identifying working scenes.
[0041] In one possible implementation, key parameters and key parameter operating ranges of the automobile controller are determined based on the real-time operating data of the automobile controller, specifically including: performing feature extraction on the real-time operating data of the automobile controller to obtain data features of the real-time operating data, and determining key parameters and key parameter operating ranges of the automobile controller based on the data features of the real-time operating data.
[0042] Specifically, the key parameters and key parameter working ranges can be determined by extracting the numerical value of the real-time working data, the numerical fluctuation range, the impact on the automobile controller and other characteristics, wherein the key parameters and key parameter working ranges of different automobile controllers are different.
[0043] For example, after feature extraction of the real-time working data of the BMS controller, the key parameters of the BMS controller can be obtained, including: operating temperature, ambient temperature, operating current, battery voltage collection value, insulation resistance, battery cell temperature collection value, PCB board temperature, and then the actual working range of each parameter is obtained to obtain the key parameter working range of the BMS controller.
[0044] Key parameters are important working parameters for automotive control. Identifying key parameters and their working range is conducive to the precise selection of subsequent chips.
[0045] It should be noted that users can perform feature extraction on the real-time working data of the automobile controller according to actual needs through different methods, such as statistics, classification, or establishing feature extraction models, etc. The embodiment of the present application does not make specific requirements for this.
[0046] S104: Determine the selection weight of the working parameters of the automobile controller according to the working scenario of the automobile controller.
[0047] In the embodiments of the present application, due to the different working scenarios of the automobile controller, the working parameters that the automobile controller needs to focus on are different. For example, the automobile controller working under high temperature has relatively high requirements for chip temperature and heat dissipation. Therefore, in the specific implementation, the selection weight of the working parameters of the automobile controller can be determined according to the working scenario of the automobile controller. In one possible implementation, the selection weight of the working parameters of the automobile controller is determined according to the working scenario of the automobile controller, specifically including: determining an initial selection weight of the working parameters of the automobile controller, adjusting the initial selection weight of the working parameters of the automobile controller based on preset rules according to the working scenario of the automobile controller, and obtaining the selection weight of the working parameters of the automobile controller.
[0048] In specific implementation, the operating parameters of the automotive controller, such as operating voltage, temperature range, power consumption, packaging type, reliability, etc., and the initial selection weight can be determined based on historical working data and industry standards.
[0049] In a specific implementation, the adjustment rules for the selection weights can be pre-set. For example, in high-temperature or severe cold working scenarios, the selection weight of the working temperature can be increased; in high-load working scenarios, the selection weight of the output load current can be increased; etc., so that after the working scenario of the automobile controller is determined, the initial selection weight of the working parameters of the automobile controller can be adjusted according to the preset rules, so that the chip selected based on the final selection weight can meet the needs of the working scenario.
[0050] For example, if the engine control module itself has a high temperature working environment and working characteristics, and if the car of this solution is mainly exported to tropical countries, then it is necessary to increase the selection weight of all key parameters of working temperature according to the working temperature and ambient temperature, so as to increase the requirement of this parameter when selecting chips. For example, when selecting driver chips, it is necessary to adjust the selection weight of the key parameter of the output current of the driver chip according to the output load current in the working scenario, so as to better meet the requirements of different scenarios.
[0051] The embodiments of the present application can dynamically adjust the selection weight of working parameters according to the working scenario, thereby improving the chip selection efficiency and selection accuracy.
[0052] S105: According to the working parameter requirements, key parameters, working ranges of key parameters and selection weights of the working parameters of the automobile controller, a chip that meets the requirements is determined from the automotive-grade chip database.
[0053] In the embodiment of the present application, when the automobile controller is working, the real-time working data will be different from the working parameter requirements recorded in the manual according to different working scenarios. Therefore, after obtaining the key parameters, key parameter working ranges and selection weights of the automobile controller, the working parameter requirements of the automobile controller can be adjusted according to the key parameters, key parameter working ranges and selection weights of the working parameters, that is, the working parameter range of the automobile controller is adjusted to obtain the target range (actual demand range) of the working parameters of the automobile controller. Then, from the automotive-grade chip database, a chip whose matching error with the target range of the working parameters of the automobile controller is within a preset range is selected, and this chip is a chip that meets the requirements.
[0054] For example, when the BMS controller is in use, surge voltage is generated under special circumstances, causing the battery cell voltage collection value to be too large and the chip pin to be impacted greatly. Therefore, it is necessary to adjust the voltage resistance parameter requirements to obtain a voltage resistance range that meets the actual voltage resistance requirements, so that an analog front-end sampling chip with a higher voltage resistance range can be selected from the automotive-grade chip database.
[0055] In a possible implementation, the preset range of the matching error can be 1% or less. Specifically, when selecting from the automotive-grade chip database, the extreme parameters and normal working parameters of the automotive controller can be matched with the chip parameters to achieve an error of 1% or less between the extreme parameters and the normal working range parameters.
[0056] The embodiment of the present application can adjust the operating parameter range of the automobile controller according to the key parameters, the operating range of the key parameters and the selection weight of the operating parameters, so that when selecting chips, accurate chip recommendations can be achieved, thereby improving the accuracy of chip selection.
[0057] The embodiment of the present application selects the chip according to the real-time working data and working parameter requirements of the automobile controller, which can adapt to the needs of different vehicle models and application scenarios, reduce manual intervention, and improve selection efficiency and accuracy.
[0058] S106: Testing the chips that meet the requirements to obtain target chips.
[0059] In the embodiment of the present application, although a chip that meets the requirements has been selected based on actual application needs, whether the selected chip can really be used in the actual working scenario still needs to be tested and verified, that is, the chip that meets the requirements is tested, and the chip that passes the test is the target chip that is ultimately required.
[0060] See also Figure 2 , is a schematic diagram of a process for testing a chip provided in an embodiment of the present application. Figure 2 As shown, the test includes the following steps.
[0061] S201: Determine chip test requirements based on target ranges of operating parameters of the automotive controller and historical operating data.
[0062] In the specific implementation, after obtaining the target range and historical working data of the working parameters of the vehicle controller, the target range and historical working data of the working parameters of the vehicle controller can be decomposed into specific chip test requirements. For example, for the power battery management system BMS, assuming that the single cell voltage acquisition accuracy is ≤±5mV, the test requirement of the AFE (analog front end) chip is to meet the accuracy deviation of ≤±5mV. For example, for the power chip, the test requirement is that the output voltage deviation of the linear regulator at full load or normal operation at high temperature cannot be greater than 5%.
[0063] S202: Generate test cases for the chip according to the chip's specification parameters and failure modes.
[0064] Based on different chips, the embodiments of the present application can combine the chip's specification parameters and failure modes to automatically generate test cases corresponding to the chip.
[0065] Specifically, for different chips, the specifications and parameters are different, and the failure modes are different. For example, the failure modes of power chips include ① overheating failure, which is caused by unreasonable heat dissipation design, excessive ambient temperature or excessive load, etc., which leads to overheating of the power chip and causes failure; ② unstable output voltage: due to improper feedback loop design or component failure, input voltage fluctuation or load change, the output voltage is unstable; ③ current overload: due to excessive load or circuit short circuit, the current overload may cause damage to the power chip; ④ output noise: due to the power design not fully considering noise suppression or the lack of sufficient filter capacitors at the input and output of the power supply, etc., output noise is caused. Therefore, the generated test cases are different.
[0066] S203: Testing the chip according to the test requirements of the chip and the test cases of the chip to obtain test results.
[0067] In the embodiment of the present application, after obtaining the test requirements of the chip and the test cases of the chip, the chip can be tested according to the generated test cases to obtain the test results.
[0068] In a possible implementation, since there may be multiple chips that meet the requirements, the following situations may be presented after testing the chips: 1. The test results of only one chip meet the test requirements; 2. The test results of at least two chips meet the test requirements; 3. The test results of all chips do not meet the test requirements. When situation 1, the chip whose test results meet the test requirements is the target chip. When situation 2 or 3, the test case needs to be further optimized so that the test results of only one chip meet the test requirements and the target chip is obtained.
[0069] Specifically, in one possible implementation, the chip is tested according to the test requirements of the chip and the test cases of the chip to obtain test results, including: testing the chip according to the test cases of the chip to obtain test results, judging whether the test results meet the test requirements of the chip; when the test results of all chips do not meet the test requirements of the chip, iteratively optimizing the test cases of the chip according to the test results until the test results of a certain chip meet the test requirements of the chip, and outputting the final test results.
[0070] Specifically, in another possible implementation, the chip is tested according to the test requirements of the chip and the test cases of the chip to obtain test results, including: testing the chip according to the test cases of the chip to obtain test results, judging whether the test results meet the test requirements of the chip, when the test results of at least two chips meet the test requirements of the chip, iteratively optimizing the test cases of the chip according to the test results until the test results of only one chip meet the test requirements of the chip, and outputting the final test results.
[0071] In a specific implementation, iterative optimization of the chip test cases according to the test results includes: looping through the following steps: S301: Analyze the test results and identify failure modes and limit conditions in the test results; In practical applications, in addition to identifying failure modes and extreme conditions in the test results, it is also necessary to identify problems and changing trends of the chip during the test. For example, during the test of the power chip, as the temperature rises and the load current increases, the output voltage deviation may be greater than 5%, the chip may overheat, and the chip output may be saturated. In this way, optimization suggestions can be provided based on the problems and changing trends of the chip during the test.
[0072] S302: Optimize the test cases of the chip according to the failure modes and extreme conditions in the test results; In the embodiment of the present application, the test case of the chip is optimized mainly to adjust the parameter range of the test case. Specifically, if the test results of multiple chips meet the test requirements, the test parameters can be tightened, such as trying to see if there are other failure modes and more stringent conditions. When the test results of no chip meet the test requirements, the test parameters can be relaxed, such as removing failure modes and extreme conditions.
[0073] In addition, when performing specific optimization, we also need to consider the problems and changing trends of the chip during testing, so that the optimized test cases meet the needs of the actual work process.
[0074] S303: Use the optimized chip test case to test the chip and obtain the test result.
[0075] The test result obtained in S303 needs to be judged continuously until the test result of one and only one chip meets the test requirement, then the iterative optimization of the test case is stopped, otherwise, S301-S303 are continued to be executed.
[0076] S204: Determine a target chip from the chips that meet the requirements according to the test results.
[0077] In an embodiment of the present application, when the test result of only one chip meets the test requirements, the obtained test result is the final test result, and the target chip can be determined from the chips that meet the requirements based on the final test result.
[0078] The embodiment of the present application can test the selected chip based on the actual working parameter requirements and perform feedback optimization on the test cases, thereby improving the comprehensiveness of the chip test, reducing the chip test cycle, and reducing the chip test cost.
[0079] The selection and testing of the automotive-grade chip of the present application is further explained below in conjunction with specific embodiments.
[0080] For example, an automobile manufacturer is developing a battery management system (BMS) for a new electric vehicle. The system needs to use an automotive-grade microcontroller that can work stably over a wide voltage range.
[0081] 1. First, collect the real-time working data and working parameter requirements of BMS, including voltage range, operating temperature, current load, etc.
[0082] 2. Through feature extraction, determine the key parameters and key parameter working range of BMS, and adjust the selection weight of working parameters according to the actual working scenario of BMS.
[0083] 3. Adjust the target range of the BMS operating parameters according to the adjusted selection weight, key parameters, key parameter operating range and operating parameter requirements; 4. Based on the target range of the adjusted BMS operating parameters, several suitable microcontroller models were selected from the automotive-grade chip database; 5. For these models, use the chip test requirement decomposition method based on work scenarios and generate specific test cases.
[0084] 6. Conduct tests in the laboratory and analyze and optimize the test results through the test case optimization mechanism.
[0085] 7. Finally, through the optimized test results, a car-grade microcontroller that is most suitable for BMS was confirmed.
[0086] Through the above embodiments, the embodiments of the present application effectively improve the efficiency of chip selection and the accuracy of compatibility testing, and provide strong support for the development of automotive electronic systems.
[0087] Corresponding to the above-mentioned embodiments, the embodiments of the present application also provide a structural schematic diagram of a selection and testing device for an automotive-grade chip.
[0088] See also Figure 3 , is a schematic diagram of the structure of a selection and testing device for an automotive-grade chip provided in an embodiment of the present application. Figure 3As shown, the selection test device 300 includes: an establishment unit 301, used to establish an automotive-grade chip database; an acquisition unit 302, used to acquire real-time working data and working parameter requirements of an automobile controller; a first determination unit 303, used to determine the working scenario, key parameters and working range of key parameters of the automobile controller according to the real-time working data of the automobile controller; a second determination unit 304, used to determine the selection weight of the working parameters of the automobile controller according to the working scenario of the automobile controller; a third determination unit 305, used to determine a chip that meets the requirements from the automotive-grade chip database according to the working parameter requirements, key parameters, working range of key parameters and selection weight of the working parameters of the automobile controller; a testing unit 306, used to test the chip that meets the requirements to obtain a target chip.
[0089] The specific contents of the embodiments of the present application can be found in the description of the above method embodiments, which will not be repeated here for the sake of brevity.
[0090] Corresponding to the above embodiment, the embodiment of the present application also provides a structural schematic diagram of a testing unit.
[0091] See also Figure 4 , is a schematic diagram of the structure of a test unit provided in an embodiment of the present application. Figure 4 As shown, the test unit 400 includes: a third determination unit 401, used to determine the test requirements of the chip according to the target range of the working parameters of the automobile controller and the historical working data; a generation unit 402, used to generate the test cases of the chip according to the specification parameters and failure modes of the chip; a test sub-unit 403, used to test the chip according to the test requirements of the chip and the test cases of the chip to obtain the test results; a fourth determination unit 404, used to determine the target chip from the chips that meet the requirements according to the test results.
[0092] Corresponding to the above embodiments, the present application also provides an electronic device.
[0093] See also Figure 5 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application, and the electronic device 500 may include: a processor 510, a memory 520, and a communication unit 530. These components communicate through one or more buses. Those skilled in the art can understand that the structure of the electronic device shown in the figure does not constitute a limitation on the embodiment of the present application. It can be a bus structure or a star structure, and can also include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.
[0094] The communication unit 530 is used to establish a communication channel so that the electronic device can communicate with other devices, receive user data sent by other devices or send user data to other devices.
[0095] The processor 510 is the control center of the electronic device. It uses various interfaces and lines to connect various parts of the entire electronic device. It runs or executes software programs, instructions, and / or modules stored in the memory 520, and calls data stored in the memory to perform various functions of the electronic device and / or process data. The processor can be composed of an integrated circuit (IC), for example, it can be composed of a single packaged IC, or it can be composed of multiple packaged ICs with the same or different functions. For example, the processor 510 can include only a central processing unit (CPU). In the embodiment of the present application, the CPU can be a single computing core or multiple computing cores.
[0096] The memory 520 is used to store execution instructions of the processor 510. The memory 520 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.
[0097] When the execution instructions in the memory 520 are executed by the processor 510, the electronic device 500 can execute some or all of the steps in each embodiment of the automotive-grade chip selection and testing method provided in the present application.
[0098] In a specific implementation, the present application also provides a computer storage medium, wherein the computer storage medium may store a program, and when the program is executed, the program may include some or all of the steps in each embodiment of the selection and testing method for automotive-grade chips provided in the embodiments of the present application. The storage medium may be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.
[0099] In a specific implementation, the present application also provides a computer program product, wherein the computer program product includes executable instructions, and when the executable instructions are executed on a computer, the computer executes part or all of the steps in each embodiment of the automotive-grade chip selection and testing method provided in the present application.
[0100] Those skilled in the art can clearly understand that the technology in the embodiments of the present application can be implemented by means of software plus a necessary general hardware platform. Based on this understanding, the technical solution in the embodiments of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a storage medium such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application or some parts of the embodiments.
[0101] In this specification, the same or similar parts between the various embodiments can be referred to each other. In particular, for the device embodiment and the terminal embodiment, since they are basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description in the method embodiment.
Claims
1. A method for selecting and testing automotive-grade chips, characterized in that: The method comprises: Establish a database of automotive-grade chips; Obtain real-time working data and working parameter requirements of the vehicle controller; Determining a working scenario, key parameters and a working range of the key parameters of the vehicle controller according to the real-time working data of the vehicle controller; Determining the selection weight of the working parameters of the automobile controller according to the working scenario of the automobile controller; According to the working parameter requirements, key parameters, working ranges of key parameters and selection weights of the working parameters of the automobile controller, a chip that meets the requirements is determined from the automotive-grade chip database; The chips meeting the requirements are tested to obtain target chips.
2. The method according to claim 1, characterized in that The determining the working scene of the automobile controller according to the real-time working data of the automobile controller includes: Inputting the real-time working data of the automobile controller into a first data model; A working scenario of the automobile controller is determined according to an output result of the first data model.
3. The method according to claim 1, characterized in that: Determining the key parameters and key parameter working ranges of the automobile controller according to the real-time working data of the automobile controller includes: Extracting features of the real-time working data of the automobile controller to obtain data features of the real-time working data; The key parameters and the key parameter working ranges of the automobile controller are determined according to the data characteristics of the real-time working data.
4. The method according to claim 1, characterized in that The determining the selection weight of the working parameters of the automobile controller according to the working scenario of the automobile controller includes: Determining the initial selection weight of the operating parameters of the vehicle controller; According to the working scenario of the automobile controller, the initial selection weight of the working parameters of the automobile controller is adjusted based on preset rules to obtain the selection weight of the working parameters of the automobile controller.
5. The method according to claim 1, characterized in that: The step of determining a chip that meets the requirements from the automotive-grade chip database according to the operating parameter requirements, key parameters, key parameter operating ranges, and selection weights of the operating parameters of the automotive controller includes: Adjusting the working parameter requirements of the automobile controller according to the key parameters, the working range of the key parameters and the selection weight of the working parameters to obtain a target range of the working parameters of the automobile controller; Obtain chips whose working parameter range in the automotive-grade chip database and the target range of the working parameters of the automotive controller have a matching error within a preset range.
6. The method according to claim 5, characterized in that The step of testing the chip that meets the requirements to obtain a target chip includes: Determining test requirements for the chip based on target ranges of operating parameters of the automotive controller and historical operating data; Generating a test case for the chip according to specification parameters and failure modes of the chip; Testing the chip according to the test requirements of the chip and the test cases of the chip to obtain a test result; A target chip is determined from the chips meeting the requirements according to the test result.
7. The method according to claim 6, characterized in that The step of testing the chip according to the test requirements of the chip and the test cases of the chip to obtain the test results includes: Testing the chip according to the test case of the chip to obtain a test result; Determining whether the test result meets the test requirements of the chip; When the test results of all chips do not meet the test requirements of the chip, iteratively optimize the test cases of the chip according to the test results until the test result of a certain chip meets the test requirements of the chip, and output the final test result; Determining a target chip from the chips meeting the requirements according to the test result includes: A target chip is determined from the chips that meet the requirements according to the final test result.
8. The method according to claim 6, characterized in that The step of testing the chip according to the test requirements of the chip and the test cases of the chip to obtain the test results includes: Testing the chip according to the test case of the chip to obtain a test result; Determining whether the test result meets the test requirements of the chip; When the test results of at least two chips meet the test requirements of the chip, iteratively optimize the test cases of the chip according to the test results until the test result of only one chip meets the test requirements of the chip, and output the final test result; Determining a target chip from the chips meeting the requirements according to the test result includes: A target chip is determined from the chips that meet the requirements according to the final test result.
9. The method according to claim 7 or 8, characterized in that: The iterative optimization of the test cases of the chip according to the test results includes: looping through the following steps: Analyzing the test results to identify failure modes and limit conditions in the test results; Optimizing test cases for the chip based on failure modes and extreme conditions in the test results; The chip is tested using the optimized test case of the chip to obtain a test result.
10. A selection and testing device for automotive-grade chips, characterized in that: include: Establish a unit for establishing a database of automotive-grade chips; An acquisition unit, used to acquire real-time working data and working parameter requirements of the automobile controller; A first determining unit, configured to determine a working scenario, key parameters, and a working range of the key parameters of the vehicle controller according to real-time working data of the vehicle controller; A second determining unit, configured to determine a selection weight of working parameters of the vehicle controller according to a working scenario of the vehicle controller; A third determining unit is used to determine a chip that meets the requirements from the automotive-grade chip database according to the working parameter requirements, key parameters, working ranges of the key parameters and the selection weights of the working parameters of the automotive controller; The testing unit is used to test the chip that meets the requirements to obtain a target chip.
11. An electronic device, characterized in that: include: processor; Memory; A computer program is stored in the memory, and when the computer program is executed, the electronic device executes the method according to any one of claims 1 to 9.
12. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 9.