Method, device, and program product for detecting the life of a vehicle component
By establishing a mapping relationship based on measured durability data, the actual operating parameters of vehicle actuators are converted into uniform life consumption values, solving the problem of inaccurate life prediction in existing technologies and achieving accurate life assessment and safe and reliable early warning.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ZHEJIANG GEELY HLDG GRP CO LTD
- Filing Date
- 2026-05-06
- Publication Date
- 2026-06-05
Smart Images
Figure CN122149885A_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the field of vehicle technology, specifically to a method, equipment, and program product for life testing of vehicle actuators. Background Technology
[0002] With the deepening development of autonomous driving technology, relevant regulations and standards have put forward clear requirements for the continuous safe operation of autonomous driving systems to ensure driving safety. These requirements include the need to monitor the lifespan of the actuators involved in vehicle control and to have the ability to issue warnings or limit functions when their lifespan is nearing its end. Against this backdrop, accurately and reliably assessing the lifespan consumption of these components during actual vehicle operation has become a key technical aspect in achieving the above requirements. Summary of the Invention
[0003] In view of this, the present disclosure provides a method, apparatus and program product for life testing of vehicle actuators, so as to accurately and reliably assess the life consumption status of vehicle actuators during actual vehicle operation.
[0004] In a first aspect, this disclosure provides a method for life testing of vehicle actuators, including: During vehicle operation, the target operating parameters of the vehicle's actuators are monitored in real time. Obtain a mapping relationship between at least one operating parameter of the vehicle actuator and a life consumption metric, wherein the mapping relationship is established based on measured durability data of the vehicle actuator; Based on the lifespan consumption metric value corresponding to the target operating parameter in the mapping relationship, the real-time monitored value of the target operating parameter is converted into an equivalent lifespan consumption value and accumulated to obtain the current lifespan consumption value reflecting the lifespan of the vehicle's actuators.
[0005] Secondly, this disclosure provides an electronic device, including: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores at least one computer program that can be executed by the at least one processor, the at least one computer program being executed by the at least one processor to enable the at least one processor to perform the life detection method for vehicle actuators as described in the first aspect.
[0006] Thirdly, this disclosure provides a computer program product, which includes a computer program that, when run in a processor, implements the life detection method for vehicle actuators described in the first aspect.
[0007] The embodiments provided in this disclosure address the problem in existing technologies where lifespan estimation based on static time or mileage fails to reflect actual dynamic operating conditions, leading to inaccurate predictions and an inability to reliably prevent lifespan risks. By employing a mapping relationship established based on measured durability data, the real-time monitored target operating parameter values are converted into equivalent lifespan consumption values under a unified benchmark and accumulated. This achieves dynamic and accurate assessment of the lifespan of vehicle actuators. This method normalizes the wear and tear caused by diverse and non-uniform operating conditions in actual operation into an accumulative equivalent lifespan consumption, enabling the lifespan assessment results to truly reflect the actual wear and tear of components under complex operating conditions. This effectively improves the accuracy of lifespan prediction and provides reliable data support for preventative maintenance and risk management of actuators. Attached Figure Description
[0008] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.
[0009] Figure 1 The diagram shown is a schematic flowchart of a life testing method for vehicle actuators in an embodiment of this disclosure.
[0010] Figure 2 The diagram shown is an exemplary flowchart of life detection and early warning for vehicle actuators in this embodiment of the present disclosure.
[0011] Figure 3 The diagram shown is a block diagram of a life detection device for vehicle actuators in an embodiment of this disclosure.
[0012] Figure 4 The diagram shown is a structural schematic of an electronic device in an embodiment of this disclosure. Detailed Implementation
[0013] The technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.
[0014] Where there is no conflict, the various embodiments of this disclosure and the features thereof in the embodiments may be combined with each other.
[0015] As used herein, the term “and / or” includes any and all combinations of one or more related enumerated entries.
[0016] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. As used herein, the singular forms “a” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that when the terms “comprising” and / or “made of” are used in this specification, the presence of the stated feature, integral, step, operation, element, and / or component is specified, but the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof is not excluded. Words such as “connected” or “linked” are not limited to physical or mechanical connections but can include electrical connections, whether direct or indirect.
[0017] Unless otherwise specified, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and this disclosure, and will not be interpreted as having an idealized or overly formal meaning, unless expressly so defined herein.
[0018] In the field of vehicle component health management technology, especially for autonomous vehicles, to accurately assess and warn of the remaining lifespan of actuators (such as braking and steering components), a common approach is to estimate lifespan based on preset fixed time intervals or total mileage. Specifically, this approach involves setting a fixed lifespan timer or mileage counter in the vehicle controller. The basic principle is that when the timer reaches a preset time or the mileage counter reaches a preset mileage threshold, the component's lifespan is considered exhausted, triggering a maintenance reminder. This method is widely used primarily because it is simple to implement, has low computational overhead, and provides a basic time or mileage reference framework for the periodic maintenance of components.
[0019] However, this solution's performance is less than ideal when applied to autonomous vehicles operating under varying loads and complex conditions. A fundamental contradiction lies in the fact that, in order to optimize its ease of implementation and versatility, the inherent design of this solution inevitably compromises the accuracy and reliability of lifespan prediction, and may even lead to safety risks associated with applications exceeding their lifespan. Specifically, in actual vehicle operation, the wear and tear of the same component after 100,000 kilometers of unloaded, normal-temperature driving differs significantly from that after 100,000 kilometers of driving on mountain roads under full load, high temperatures, and frequent braking. If both are warned based on the same 100,000-kilometer threshold, the former may trigger an early warning, causing unnecessary maintenance, while the latter may trigger an late warning, resulting in performance degradation of the component before reaching the threshold, thus failing to meet the safety requirements of autonomous driving functions.
[0020] To address this issue, this disclosure proposes a lifespan detection method for vehicle actuators. The core concept lies in introducing a transformation relationship based on measured durability data, mapping multi-dimensional dynamic operating parameters to a unified lifespan consumption metric. This improves the core aspect of lifespan accumulation, effectively enhancing the accuracy of lifespan assessment without significantly increasing system complexity. It also avoids the risk of exceeding lifespan limits due to inaccurate predictions, thus resolving the problem of inaccurate lifespan detection caused by ignoring actual operating condition differences in related technologies. This achieves a refined and adaptive assessment of the actual wear and tear status of vehicle actuators.
[0021] The lifespan detection method for vehicle actuators provided in this disclosure can be applied to a vehicle controller, or to other terminals or servers capable of communicating with the vehicle and / or sensors installed on the vehicle. In an exemplary application architecture, the lifespan detection method is applied inside the vehicle and may include a sensing layer, a processing layer, and an execution layer. The sensing layer is responsible for real-time acquisition of vehicle operating data, which may include, but is not limited to: wheel speed sensors or odometers for monitoring vehicle mileage; exterior temperature sensors for monitoring ambient temperature; sensors for indirectly or directly estimating vehicle load, such as suspension height sensors, seat weight sensors, or camera-based people recognition systems; and sensors for monitoring the operating status of actuators, such as brake fluid pressure sensors, steering torque sensors, and motor current sensors. The processing layer typically consists of one or more domain controllers (e.g., chassis domain controllers) or dedicated computing units, configured with a processor and memory, for running the lifespan detection method provided in this disclosure. The processing layer receives real-time operating parameters from the sensing layer and calls pre-stored mapping relationships to calculate and accumulate lifespan consumption. The execution layer, based on the lifespan status assessment results output by the processing layer, executes corresponding warning or control strategies. For example, it may issue maintenance reminders or caution warnings to the driver via the in-vehicle instrument panel, central control screen, or voice system, or send function limitation commands to the vehicle control system in extreme cases. It is understood that data interaction between the above layers can be accomplished through the vehicle's internal controller area network bus, Ethernet, or other in-vehicle communication networks. In some embodiments, the storage and updating of some data processing or mapping relationships can also be assisted by vehicle-to-cloud communication on a remote server.
[0022] The technical terms used in the embodiments of this disclosure are explained as follows: "Lifespan metric" refers to a unified, dimensionless, or dimensionlessly quantifiable numerical indicator used to quantify the lifespan loss of components. Its core function is to provide a common, linearly cumulative benchmark for the various forms of lifespan loss occurring under different operating conditions. For example, it can be expressed as a percentage, representing the proportion of lifespan already consumed to the total lifespan; or it can be expressed as an equivalent baseline mileage, representing the mileage traveled under a specific standard operating condition after adjusting for actual consumption.
[0023] "Application conditions" refer to external conditions or vehicle status parameters that affect the rate of component lifespan consumption. They do not directly represent the amount of component movement, but they modulate the degree to which the amount of movement affects the lifespan. For example, ambient temperature, vehicle load gear, and road gradient all fall under the category of application conditions.
[0024] "Lifespan consumption operating parameters" refer to parameters that directly reflect the "amount" of work done by a component, and their accumulation is directly related to the mechanical or electrical wear of the component. Examples include vehicle mileage, the integral of the intensity and duration of braking actions, and the number of times a specific function is triggered.
[0025] "Final application state" refers to the critical state where a component's lifespan has ended and maintenance or replacement is required. This does not mean the component has completely failed, but rather that its performance indicators (such as brake pad thickness and steering clearance) have deteriorated to a threshold state where they can no longer meet the functional safety requirements of the autonomous driving system. This state is determined through durability testing.
[0026] Figure 1 The diagram shown is a schematic flowchart of a life detection method for vehicle actuators according to an embodiment of the present disclosure. This method can be executed by an on-board electronic device, such as a processor in a chassis domain controller; of course, it can also be executed by other terminals or servers, without limitation. The method mainly includes the following steps: Step 101: During vehicle operation, monitor the target operating parameters of the vehicle's actuators in real time.
[0027] Target operating parameters refer to operating parameters that have a significant impact on the lifespan of the actuator. They broadly refer to any measurable or estimable parameter that can reflect the operating status of the component or its environment.
[0028] As a specific implementation method, the target operating parameters can include application conditions and lifespan consumption parameters. For example, for a braking system, application conditions can include real-time ambient temperature and the vehicle's current load level (e.g., no load, half load, full load), while lifespan consumption parameters can include real-time mileage. This approach allows for the separate consideration of external conditions and internal dynamic quantities, laying the foundation for establishing a refined mapping relationship, because the same dynamic quantity leads to different lifespan consumption under different application conditions.
[0029] For example, real-time monitoring of target operating parameters can be achieved through various onboard sensors and controllers. Specific methods may include: acquiring cumulative mileage via wheel speed sensors and the vehicle network; acquiring ambient temperature via an outside temperature sensor; estimating vehicle load based on changes in suspension height sensor signals or seat occupancy signals, and categorizing it into several preset discrete gears (e.g., neutral, half, and full); reading brake pressure values in real time via a brake fluid pressure sensor; and acquiring trigger signals from the anti-lock braking system or electronic parking brake via the controller area network bus. This sensor data is transmitted via the vehicle bus to a processor that executes the lifespan detection algorithm.
[0030] In a specific example, the real-time monitoring process is continuous. For instance, the mileage parameter is updated every kilometer the vehicle travels; the temperature parameter can be sampled every minute or updated when the change exceeds a certain threshold; the vehicle load level can be reassessed and updated each time the vehicle is powered on or when there is a significant change in the number of passengers; and the braking pressure is recorded in real time every time braking occurs. The monitored parameter values are temporarily stored in a specific area of memory for subsequent calculations.
[0031] Step 102: Obtain the mapping relationship between at least one operating parameter of the vehicle actuator and the life consumption metric, wherein the mapping relationship is established based on the measured durability data of the vehicle actuator.
[0032] For example, the mapping relationship can be a predefined data table, function, or set of coefficients that establishes a correspondence between specific operating parameter values (or combinations of parameters) and a unified lifetime consumption metric. This mapping relationship defines the conversion rules for transforming diverse operating parameters into a unified lifetime consumption scale.
[0033] As a specific implementation, this mapping relationship can be represented as a multidimensional lookup table or a set of calculation formulas. For example, for the case where mileage is used as the operating parameter for vehicle lifespan consumption, the mapping relationship can be a table containing the "equivalent lifespan consumption metric value corresponding to each actual kilometer driven" under different temperatures and load levels. This mapping relationship can be obtained by pre-setting a data table, calibrated through extensive durability testing, in the non-volatile memory of the vehicle controller before the vehicle leaves the factory. During vehicle operation, the processor retrieves the conversion coefficients corresponding to the current parameter combination by querying this pre-stored data table.
[0034] For example, the establishment of the mapping relationship relies on measured durability data, rather than theoretical simulation. The process typically includes: planning durability tests covering different application conditions (such as high, medium, and low temperatures, and different loads) during the design phase for a specific actuator; allowing the component to operate continuously under different combinations of conditions and monitoring its performance degradation until it reaches its final application state; recording the total amount of accumulated lifespan consumption parameters (e.g., total mileage, total pressure-time integral value, total number of triggers) when reaching the final application state under each combination of conditions; and finally, using a selected baseline condition as a reference, calculating the lifespan consumption ratio of other combinations of conditions relative to that baseline condition, thus forming the mapping relationship. This approach ensures the accuracy of the model because it is directly derived from wear data in the physical world.
[0035] In a specific example, for a brake caliper (such as a friction pad), engineers conduct durability bench tests in the laboratory under three ambient temperatures (high temperature, normal temperature, and low temperature) and three simulated loads (no load, half load, and full load). The tests show that under the normal temperature no-load baseline condition, the brake caliper reaches its final application state (e.g., friction pad wear to 3 mm) with an equivalent standard mileage of 600,000 kilometers. However, under the high temperature full load condition, the actual mileage at the same final application state might only be 200,000 kilometers. Based on this, the lifespan consumption ratio under the high temperature full load condition relative to the baseline condition can be calculated as 60 / 20 = 3.0. This means that for every kilometer actually driven under high temperature full load, the resulting lifespan consumption is equivalent to driving 3 kilometers under the baseline condition. All these coefficients are organized and stored in a mapping table.
[0036] Step 103: Based on the life consumption metric value corresponding to the target operating parameter in the mapping relationship, convert the real-time monitored value of the target operating parameter into an equivalent life consumption value and accumulate it to obtain the current life consumption value that reflects the life of the vehicle's actuator.
[0037] Using the mapping relationship obtained in step 102, the "original" lifespan consumption operating parameter values collected in step 101 under specific application conditions are converted into a unified, linearly superimposed "equivalent" lifespan consumption value. This value is then continuously accumulated to obtain the total lifespan consumption from the start of use to the present.
[0038] As a specific implementation method, conversion and accumulation can be achieved through periodic calculations. For example, every time the processor accumulates a certain mileage (e.g., 10 kilometers) or every fixed time period (e.g., 1 hour), it looks up the corresponding "lifetime consumption value per unit of operating parameter" (i.e., conversion coefficient) from the mapping relationship based on the average or dominant application conditions (e.g., average temperature, main load level) during that mileage or time period. Then, it multiplies the accumulated lifetime consumption operating parameter value (e.g., 10 kilometers) during that mileage or time period by the conversion coefficient to obtain the equivalent lifetime consumption value for that mileage or time period, and finally adds this value to the total lifetime consumption value.
[0039] To handle dynamically changing application conditions, a more refined accumulation strategy can be employed. Specifically, lifespan consumption parameters corresponding to different application conditions can be obtained from the real-time monitored target operating parameters. Then, a unified lifespan consumption metric corresponding to the lifespan consumption parameters under different application conditions can be obtained from the mapping relationship. The lifespan consumption parameter value for each application condition is multiplied by the lifespan consumption metric for that condition to obtain the lifespan consumption value for each application condition. Finally, the lifespan consumption values for different application conditions are accumulated to obtain the current lifespan consumption value reflecting the lifespan of the vehicle's actuators. For example, during a trip, the vehicle may experience 10 kilometers of unloaded normal temperature driving, 5 kilometers of fully loaded high temperature driving, and 3 kilometers of half-load low temperature driving. The processor will calculate the lifespan consumption for the unloaded normal temperature portion as 10 kilometers. (Unloaded normal temperature coefficient 1.0); Full load high temperature part consumption = 5 kilometers (Full load high temperature coefficient 3.0); Half load low temperature consumption = 3 kilometers (Half-load low temperature coefficient 1.5). Then add these three consumption values together to obtain the total equivalent life consumption of this trip.
[0040] In a specific example, assume the total equivalent mileage under the baseline operating condition (no load and normal temperature) is S_base = 600,000 km. Historical driving data is monitored as follows: S_normal_no load = 300,000 km at normal temperature with no load, S_high_full_load = 10,000 km at high temperature with full load, and S_low_half_load = 50,000 km at low temperature with half load. From the pre-stored mapping table, the lifespan consumption metric for the high temperature full load condition is K_high_full_load = 3.0, and for the low temperature half-load condition is K_low_half_load = 1.2. Therefore, the cumulative equivalent lifespan consumption value (expressed as equivalent baseline mileage) is: Cumulative Send = S_normal_no load. 1.0 + S_High Full K_High Full + S_Low Half K_low half = 300,000 + 10,0003.0 + 50,0001.2 = 300,000 + 30,000 + 60,000 = 390,000 kilometers. The current lifespan consumption ratio is 390,000 / 600,000 = 65%.
[0041] To further optimize the precision and applicability of the lifespan assessment in the above embodiments and address specific issues arising from different component types, this disclosure provides various specific implementation methods. As mentioned above, the target operating parameters may include application conditions and lifespan consumption operating parameters. The mapping relationship includes the lifespan consumption metric values corresponding to the lifespan consumption operating parameters under different application conditions. This limitation aims to structure multi-dimensional influencing factors, making the establishment and application of mapping relationships more systematic and scalable. The specific establishment methods for several typical lifespan consumption operating parameters and their mapping relationships will be described in detail below.
[0042] Method 1 addresses the scenario where the lifespan consumption parameter is the vehicle's mileage. In this case, the application conditions typically include ambient temperature and vehicle load level, with at least two discrete levels, such as no load, half load, and full load. In this preferred embodiment, the mapping relationship is established by: conducting durability tests on vehicle components at different ambient temperatures to determine the total mileage at which they reach their final application state under different vehicle load levels; for combinations of different vehicle load levels and different ambient temperatures, determining the lifespan consumption ratio coefficient of this combination relative to a benchmark combination consisting of a benchmark load level and a benchmark ambient temperature, based on the total mileage at which the combination reaches its final application state; and determining the lifespan consumption metric value corresponding to the combination based on the lifespan consumption ratio coefficient, thus obtaining the mapping relationship. This design allows the lifespan consumption ratio coefficient to directly reflect the severity of component wear under the given conditions. Those skilled in the art will understand that the benchmark combination can be arbitrarily chosen, typically the most common or data-stable combination, such as ambient temperature no load. The method for determining the ratio coefficient is to divide the total lifespan mileage of the benchmark combination by the total lifespan mileage of the current combination.
[0043] Specifically, the lifespan consumption ratio coefficient is the lifespan consumption metric. Assuming a normal temperature no-load condition is chosen as the baseline, its total lifespan mileage S_base is 600,000 kilometers. Durability tests show that the total lifespan mileage under high-temperature full-load conditions, S_high_full, is 200,000 kilometers. Therefore, the lifespan consumption ratio coefficient K_high_full under high-temperature full-load conditions = S_base / S_high_full = 60 / 20 = 3.0. This means that in the mapping relationship, for every kilometer actually driven under high-temperature full-load conditions, the corresponding lifespan consumption metric (equivalent baseline mileage) is 3.0 kilometers. In real-time calculations, as long as the vehicle is under high-temperature full-load conditions, every kilometer driven will be added to the total equivalent lifespan consumption with a weight of 3.0. The number of temperature and load levels mentioned above is not limited to three levels (high, medium, and low) and three levels (empty, half, and full). It can be divided into finer or coarser levels based on component characteristics and verification costs. The specific value of the ratio coefficient will also vary depending on the component model and material manufacturing process.
[0044] Method two addresses the scenario where the lifespan consumption parameters are the intensity and duration of the vehicle's actuators' movements. This applies to components with continuous movements, such as steering systems and linear braking. In this case, the operating conditions typically include ambient temperature. The mapping process in this method involves: conducting durability tests on the vehicle's actuators under different ambient temperatures to determine the total duration of movement when different intensities reach their final application state; and determining the integral value of each intensity and its corresponding total duration when the vehicle's actuator reaches its final application state. For combinations of different intensities and ambient temperatures, based on the integral value corresponding to the combination reaching its final application state, a lifespan consumption ratio coefficient is determined relative to a baseline combination composed of a baseline intensity and a baseline ambient temperature. Based on this lifespan consumption ratio coefficient, the lifespan consumption metric value corresponding to the combination is determined, thus obtaining the mapping relationship. Intensity can be brake fluid pressure, steering torque, etc. The integral value reflects the combined effect of "force" and "time," better reflecting the fatigue wear of the component.
[0045] Specifically, the lifespan consumption ratio is the lifespan consumption metric. Taking a braking system as an example, the action intensity is the brake fluid pressure P. A durability test is conducted at room temperature, recording the cumulative action duration under different pressure ranges when the braking system reaches its final application state, and calculating the total integral value I_base = Σ(P_i t_i). Then, the same test is conducted at high temperature to obtain the total integral value I_high when the same final state is reached. Therefore, the lifespan consumption ratio K_high under high temperature conditions relative to the baseline conditions is K_high = I_base / I_high. During real-time calculation, the system continuously monitors the brake fluid pressure P and the duration Δt of a single braking action, calculating the infinitesimal integral ΔI = P. Δt. Based on the current ambient temperature, select the corresponding lifespan consumption ratio K, then the equivalent lifespan consumption value for this braking action is ΔI. K is then summed. The intensity of the action can also be divided into several discrete intervals (such as light braking, medium braking, and heavy braking) to simplify the mapping table. The integral calculation can be approximated by summing after discrete sampling in the time domain.
[0046] For different actuators, the intensity of action can be braking intensity, steering intensity, driving intensity, bump intensity (flat road or bumpy road), power intensity, etc.
[0047] Method 3 addresses situations where the target operating parameter is the number of triggers of vehicle actuators. This applies to discrete triggering functions such as Electronic Stability Control (ESC) triggering, Anti-lock Braking System (ABS) braking, Automatic Emergency Braking (AEB), parking actions, or gear shifting actions. In this case, the application condition includes the intensity of the action or environmental conditions associated with the number of triggers. The baseline application condition includes the baseline intensity of the action or baseline environmental conditions associated with the baseline number of triggers. The process of establishing the mapping relationship specifically includes: determining the total number of triggers when the vehicle actuators reach their final application state under different application conditions through durability testing; determining the life consumption ratio coefficient of different application conditions relative to the baseline application condition based on the total number of triggers under different application conditions; and converting the life consumption value of a single trigger under different application conditions into a life consumption metric value based on this life consumption ratio coefficient to obtain the mapping relationship.
[0048] Specifically, taking electronic parking brake as an example, its application conditions can include ambient temperature and parking force (corresponding to different slopes). Under the baseline condition of normal temperature and low force, the total number of triggers F_base_small is measured when the final application state is reached. Under the baseline condition of high temperature and high force, the total number of triggers F_high_large is measured. Then, the life consumption value K of a single trigger under the high temperature and high force condition relative to the baseline condition is K = F_base_small / F_high_large. In real-time monitoring, whenever parking brake is applied, the current ambient temperature and estimated slope (determining the required force) are determined, and the corresponding life consumption metric K is retrieved from the mapping table. Then, this trigger is counted as consuming K units of life consumption metric value (with the single trigger consumption under the baseline condition as unit 1). By adopting the above specific limitations on different types of operating parameters and their mapping relationships, this implementation method can achieve accurate life modeling for components with different working modes such as linear continuous action and discrete trigger action. This further helps to solve the problem of difficulty in unified evaluation caused by the diversity of component working modes, thereby synergistically strengthening the core technical effect of the present invention to achieve accurate life assessment through normalized accumulation. Furthermore, it is understandable that, based on this, combining the mapping relationships of different components with the cumulative method can enable comprehensive life health management of multiple key execution components of the entire autonomous driving system.
[0049] In one specific implementation, after obtaining the current lifespan consumption value of the vehicle's actuators based on any of the three methods provided above, in order to provide intuitive feedback to the user and take necessary safety measures, after obtaining the current lifespan consumption value reflecting the lifespan of the vehicle's actuators, the method further includes: converting the current lifespan consumption value into an equivalent remaining driving mileage, comparing the equivalent remaining driving mileage with a preset mileage threshold, and triggering an alarm or function restriction strategy based on the comparison result. The purpose of this limitation is to transform the internally calculated, potentially abstract lifespan consumption value into intuitive information that is easy for the driver to understand and focus on, such as "how many kilometers can I still drive?"
[0050] For example, the conversion process can be implemented using the total lifespan equivalent mileage under the baseline application conditions in the mapping relationship. For instance, assuming the total lifespan equivalent mileage of a component under the baseline conditions is known to be L_total_base, and the current accumulated equivalent lifespan consumption value (expressed as equivalent baseline mileage) is L_consumed, then the equivalent remaining mileage L_remaining = L_total_base - L_consumed. The system can preset two levels of warning thresholds: the first level threshold (e.g., remaining mileage less than 10,000 km) is used to trigger a maintenance reminder; the second, more stringent threshold (e.g., remaining mileage less than 2,000 km) is used to trigger a severe warning that the function is about to be disabled, reminding the user to drive cautiously and have it repaired immediately. The alarm methods can include dashboard icon illumination, text messages, voice prompts, etc. Function restriction strategies may include limiting the vehicle's maximum speed, disabling autonomous driving functions, or restricting their operating scenarios (e.g., allowing use only at low speeds). By adopting the above warning strategies, tiered warnings can be provided when the component's lifespan is nearing its end, giving users sufficient time to prepare for maintenance while providing stronger safety intervention when risks are imminent, effectively balancing safety and user experience. The warning threshold here (e.g., 10,000 kilometers) is not a fixed value; it can be set proportionally based on the total lifespan of the component, for example, as 5% or 1% of the total lifespan. Understandably, this warning strategy can be used in conjunction with any one or more of the aforementioned lifespan accumulation methods.
[0051] In a specific implementation, such as Figure 2 The diagram illustrates an exemplary process for vehicle component lifespan detection and early warning. The current lifespan consumption value of each component is obtained using methods one, two, and three, and the equivalent remaining mileage corresponding to the current lifespan consumption value is determined. It then determines whether the equivalent remaining mileage is less than 10,000 kilometers. If not, the vehicle is reminded that a fault needs to be detected, and that it is currently capable of normal driving; this reminder continues unless a fault is detected. If a fault is detected, the vehicle is reminded that the expected remaining lifespan is less than 10,000 kilometers, a repair request is made, and a warning to drive cautiously is issued; this reminder continues unless a fault is detected.
[0052] In summary, the lifespan detection method for vehicle actuators provided in this disclosure addresses the problem in existing technologies where lifespan estimations based on static time or mileage fail to reflect actual dynamic working conditions, leading to inaccurate predictions and an inability to reliably prevent lifespan risks. By employing a mapping relationship established based on measured durability data, the method converts real-time monitored target operating parameter values into equivalent lifespan consumption values under a unified benchmark and accumulates them, thereby achieving a dynamic and accurate assessment of the lifespan of vehicle actuators. This method normalizes the wear and tear caused by diverse and non-uniform working conditions in actual operation into an accumulative equivalent lifespan consumption, ensuring that the lifespan assessment results truly reflect the actual wear and tear of components under complex operating conditions. This effectively improves the accuracy of lifespan prediction and provides reliable data support for preventative maintenance and risk management of actuators.
[0053] Furthermore, this method transforms vehicle health management from passive, fixed-cycle maintenance to proactive, precise early warning based on actual wear and tear. Users can clearly understand the true condition of components, avoiding safety hazards caused by insufficient mileage under harsh operating conditions, and also preventing waste from prematurely replacing components in good working conditions. Through continuous learning and accumulation, a balance between safety and economy is ultimately achieved.
[0054] It is understood that the various method embodiments mentioned above in this disclosure can be combined with each other to form combined embodiments without violating the principle and logic. Due to space limitations, this disclosure will not elaborate further. Those skilled in the art will understand that in the above methods of specific implementation, the specific execution order of each step should be determined by its function and possible internal logic, and the execution order between steps is not limited to implementation according to step number.
[0055] In addition, this disclosure also provides apparatus, electronic equipment, and computer program products, all of which can be used to implement any of the vehicle actuator life detection methods provided in this disclosure. The corresponding technical solutions and descriptions are described in the corresponding descriptions in the method section and will not be repeated here.
[0056] Figure 3 This is a block diagram of a life detection device for a vehicle actuator provided in an embodiment of the present disclosure. The life detection device for the vehicle actuator mainly includes: The monitoring module 301 is used to monitor the target operating parameters of the vehicle's actuators in real time during vehicle operation. The acquisition module 302 is used to acquire the mapping relationship between at least one operating parameter of the vehicle actuator and the life consumption metric value, wherein the mapping relationship is established based on the measured durability data of the vehicle actuator. The processing module 303 is used to convert the real-time monitored value of the target operating parameter into an equivalent life consumption value and accumulate it according to the life consumption metric value corresponding to the target operating parameter in the mapping relationship, so as to obtain the current life consumption value of the vehicle execution component.
[0057] Figure 4 This is a block diagram of an electronic device provided in an embodiment of the present disclosure.
[0058] Reference Figure 4 This disclosure provides an electronic device, which includes: at least one processor 401; at least one memory 402; and one or more I / O interfaces 403 connected between the processor 401 and the memory 402; wherein the memory 402 stores one or more computer programs that can be executed by the at least one processor 401, and the one or more computer programs are executed by the at least one processor 401 to enable the at least one processor 401 to perform the above-described life detection method for vehicle actuators.
[0059] The modules in the aforementioned electronic devices can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.
[0060] This disclosure also provides a computer program product, including a computer program that, when run in a processor, implements the aforementioned life detection method for vehicle actuators.
[0061] The computer program may be stored on a readable storage medium of a computer device or in the cloud; the processor of the computer device reads the computer program from the readable storage medium or in the cloud.
[0062] The aforementioned computer program product can be implemented through hardware, software, or a combination thereof. In one optional embodiment, the computer program product is specifically manifested as a computer storage medium; in another optional embodiment, the computer program product is specifically manifested as a software product, such as a software development kit (SDK), etc.
[0063] Those skilled in the art will understand that all or some of the steps, systems, and apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software can be distributed on a computer-readable storage medium, which may include computer storage media (or non-transitory media) and communication media (or transient media).
[0064] As is known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable program instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), static random access memory (SRAM), flash memory or other memory technologies, portable compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, it is known to those skilled in the art that communication media typically contain computer-readable program instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.
[0065] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.
[0066] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages such as Smalltalk, C++, etc., and conventional procedural programming languages such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.
[0067] The computer program product described herein can be implemented specifically through hardware, software, or a combination thereof. In one alternative embodiment, the computer program product is specifically embodied in a computer storage medium; in another alternative embodiment, the computer program product is specifically embodied in a software product, such as a software development kit (SDK), etc.
[0068] Various aspects of this disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.
[0069] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.
[0070] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.
[0071] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.
[0072] The above description is merely a preferred embodiment of this disclosure and is not intended to limit this disclosure. Any modifications or equivalent substitutions made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.
Claims
1. A method for life testing of vehicle actuators, characterized in that, include: During vehicle operation, the target operating parameters of the vehicle's actuators are monitored in real time. Obtain a mapping relationship between at least one operating parameter of the vehicle actuator and a life consumption metric, wherein the mapping relationship is established based on measured durability data of the vehicle actuator; Based on the lifespan consumption metric value corresponding to the target operating parameter in the mapping relationship, the real-time monitored value of the target operating parameter is converted into an equivalent lifespan consumption value and accumulated to obtain the current lifespan consumption value reflecting the lifespan of the vehicle's actuators.
2. The method according to claim 1, characterized in that, The target operating parameters include application conditions and lifespan consumption operating parameters; The mapping relationship includes the lifespan consumption metric value corresponding to the lifespan consumption operating parameters under different application conditions.
3. The method according to claim 2, characterized in that, The application conditions include ambient temperature and vehicle load level, and the vehicle load level includes at least two discrete levels; the lifespan consumption operating parameters include vehicle mileage. The process of establishing the mapping relationship includes: Durability tests were conducted on the vehicle's actuators under different ambient temperatures to determine the total mileage when reaching the final application state under different vehicle load levels. For different combinations of vehicle load gears and different ambient temperatures, based on the total mileage when the combination reaches its final application state, the life consumption ratio coefficient of the combination relative to the benchmark combination composed of the benchmark load gear and benchmark ambient temperature is determined. Based on the life consumption ratio coefficient corresponding to the combination, the life consumption metric value corresponding to the combination is determined, and the mapping relationship is obtained.
4. The method according to claim 2, characterized in that, The lifespan consumption operating parameters include the intensity and duration of the actions of the vehicle's actuators; The application conditions include ambient temperature; The process of establishing the mapping relationship includes: Durability tests were conducted on the vehicle actuators under different ambient temperatures to determine the total duration of action when different action intensities reached the final application state, and the integral value of each action intensity and the corresponding total duration of action when the vehicle actuators reached the final application state was determined respectively. For combinations of different action intensities and different ambient temperatures, based on the integral value corresponding to the combination when reaching the final application state, the life consumption ratio coefficient of the combination relative to the benchmark combination composed of the benchmark action intensity and benchmark ambient temperature is determined. Based on the life consumption ratio coefficient corresponding to the combination, the life consumption metric value corresponding to the combination is determined, and the mapping relationship is obtained.
5. The method according to claim 2, characterized in that, The target operating parameters include the number of times the vehicle's actuators are triggered; the application conditions include the intensity of motion or environmental conditions associated with the number of triggers; the benchmark application conditions include the benchmark intensity of motion or benchmark environmental conditions associated with the benchmark number of triggers. The process of establishing the mapping relationship includes: The total number of triggers when the vehicle actuators reach their final application state under different application conditions is determined through durability testing. Based on the total number of triggers under different application conditions, the lifetime consumption ratio coefficient of different application conditions relative to the baseline application condition is determined. Based on the lifetime consumption ratio coefficient, the lifetime consumption value of a single trigger under different application conditions is converted into a lifetime consumption metric value to obtain the mapping relationship.
6. The method according to claim 5, characterized in that, The vehicle actuator is an actuator that generates trigger-type actions, including triggering of the electronic stability control system, braking of the anti-lock braking system, automatic emergency braking, parking action, or gear shifting action.
7. The method according to any one of claims 1-6, characterized in that, After obtaining the current lifespan consumption value reflecting the lifespan of the vehicle's actuators, the method further includes: The current lifespan consumption value is converted into an equivalent remaining driving mileage, and the equivalent remaining driving mileage is compared with a preset mileage threshold. Based on the comparison result, an alarm or function restriction policy is triggered.
8. The method according to any one of claims 2-6, characterized in that, The step of converting the real-time monitored values of the target operating parameters into equivalent lifespan consumption values and accumulating them according to the lifespan consumption metric values corresponding to the target operating parameters in the mapping relationship to obtain the current lifespan consumption value reflecting the lifespan of the vehicle's actuators includes: From the target operating parameters monitored in real time, obtain the life consumption operating parameters corresponding to different application conditions; The lifespan consumption metric value corresponding to the lifespan consumption operating parameter under different application conditions is obtained from the mapping relationship. The lifespan consumption operating parameter value corresponding to each application condition is multiplied by the lifespan consumption metric value to obtain the lifespan consumption value of each application condition. The lifespan consumption values of different application conditions are accumulated to obtain the current lifespan consumption value reflecting the lifespan of the vehicle's actuator.
9. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores at least one computer program that can be executed by the at least one processor, the at least one computer program being executed by the at least one processor to enable the at least one processor to perform the life detection method for vehicle actuators as claimed in any one of claims 1-8.
10. A computer program product, characterized in that, The computer program product includes a computer program that, when run in a processor, implements the life detection method for vehicle actuators as described in any one of claims 1-8.