A control method of an epb product combining vehicle speed and wheel speed

Abstract

The application provides a control method of an EPB product combining vehicle speed and wheel speed, relates to the technical field of vehicle control, and judges a vehicle stable state through an ESC, collects vehicle speed according to vehicle stable state information, further obtains dynamic and static parking determination information, and triggers an EPB control instruction according to the dynamic and static parking determination information; vehicle speed state analysis is performed, clamping force data is generated according to vehicle speed analysis data, clamping force adjustment is performed, wheel speed information in the adjustment process is obtained, abnormal wheel determination is performed and wheel brake control data is generated; clamping force data adjustment analysis is performed according to the wheel brake control data in combination with wheel speed attenuation rate, clamping force adjustment analysis data is obtained, and then vehicle speed adjustment data is obtained. Static parking adjustment is performed according to the vehicle speed analysis data and the wheel analysis data, static parking adjustment data is obtained, and the application can realize abnormal accurate positioning and control optimization adjustment of vehicle braking.

Description

Technical Field

[0001] This invention proposes a control method for EPB products that combines vehicle speed and wheel speed, relating to the field of vehicle control technology, specifically to the field of control technology for EPB products that combine vehicle speed and wheel speed. Background Technology

[0002] Current EPB control systems largely rely on setting clamping force based on a single vehicle speed parameter, which can easily lead to compatibility issues: insufficient clamping force during dynamic and static parking results in excessively long braking distances, while excessive clamping force causes jerking. Existing technologies are also crude in their judgment of abnormal wheel conditions, often relying on indirect assessments based on overall vehicle speed fluctuations. This makes it difficult to accurately identify individual wheel slippage or lock-up tendencies, increasing the risk of brake veer. Furthermore, the lack of a braking performance feedback optimization mechanism means that the clamping force cannot be dynamically adjusted based on the vehicle speed fade rate, making it difficult to balance braking safety and comfort. Summary of the Invention

[0003] This invention provides a control method for EPB products that combines vehicle speed and wheel speed to solve the above-mentioned problems:

[0004] This invention proposes a control method for an EPB product that combines vehicle speed and wheel speed, the method comprising:

[0005] S1. Determine the vehicle's stability status through ESC, collect vehicle speed based on the vehicle stability status information, and then obtain dynamic and static parking judgment information. Trigger EPB control command based on the dynamic and static parking judgment information.

[0006] S2. Based on the dynamic and static parking judgment information and the EPB control command, analyze the vehicle speed status, generate clamping force data based on the vehicle speed analysis data, adjust the clamping force, obtain the wheel speed information during the adjustment process, judge abnormal wheels and generate wheel braking control data.

[0007] S3. Based on the wheel braking control data and the wheel speed attenuation rate, perform clamping force data adjustment analysis to obtain clamping force adjustment analysis data, and then obtain vehicle speed adjustment data.

[0008] S4. Dynamic and static parking judgment information: Analyze the vehicle speed and wheels for static parking, and adjust the static parking based on the vehicle speed analysis data and wheel analysis data to obtain static parking adjustment data.

[0009] Further, S1 includes:

[0010] Obtain communication status information from ESC via EPB to obtain ESC status information;

[0011] Compare the ESC status information with the preset ESC status threshold; ESC status comparison information.

[0012] Based on the ESC status comparison information, the ESC status is determined to obtain the ESC status determination information.

[0013] Based on the ESC status determination information, vehicle speed is collected to obtain vehicle speed data.

[0014] When the ESC status determination information is unqualified, the vehicle speed is collected;

[0015] The vehicle speed data is compared with a preset vehicle speed threshold to obtain a vehicle speed comparison result.

[0016] Based on the vehicle speed comparison results, dynamic and static parking determination is performed to obtain dynamic and static parking determination information.

[0017] The EPB control command is triggered based on the dynamic and static parking determination information.

[0018] Further, S2 includes:

[0019] When the EPB receives the EPB control command and the dynamic and static parking judgment information is dynamic parking, it collects the vehicle's longitudinal speed to obtain dynamic speed data.

[0020] Based on the dynamic vehicle speed data, the vehicle speed status is determined to obtain vehicle speed status determination information.

[0021] Based on the vehicle speed status determination information, corresponding clamping force data is generated, and dynamic vehicle speed data adjustment is performed.

[0022] Obtain the wheel speed difference data between each wheel of the vehicle and other wheels, and obtain three wheel speed difference data for each wheel;

[0023] The wheel speed difference data of the three wheels of each wheel are analyzed to determine the vehicle driving status and obtain vehicle driving status judgment information.

[0024] Wheel braking control data is generated based on the vehicle driving status judgment information.

[0025] When the vehicle driving status determination information indicates an abnormal driving status, wheel braking control data is generated based on the wheel status comparison information.

[0026] When the vehicle driving status determination information is normal driving status, wheel monitoring weight information is generated based on wheel status comparison information, wheel status weight monitoring is performed, and wheel status monitoring information is obtained.

[0027] Furthermore, the analysis of wheel speed differences based on the three wheel speed difference data for each wheel, and the subsequent determination of the vehicle's driving state to obtain vehicle driving state determination information, includes:

[0028] Sort the three wheel speed difference data for each wheel to obtain the first wheel speed difference sequence;

[0029] Obtain all first-round speed difference sequences for all wheels, and based on all first-round speed difference sequences, obtain the wheel speed difference of the first-ranked wheel for each wheel;

[0030] Sort the wheel speed differences of the first-ranked wheels among multiple wheels to obtain the second wheel speed difference sequence;

[0031] Obtain the speed difference interval data between adjacent wheels based on the second round speed difference sequence;

[0032] The adjacent wheel speed difference interval data is compared with a preset wheel speed difference interval threshold to obtain the wheel speed difference interval comparison result;

[0033] Based on the comparison result of the wheel speed difference interval, the second wheel speed difference sequence is broken, and the wheel speed difference of the wheel that is sorted first after the break is obtained and determined to be an abnormal wheel speed difference.

[0034] The number of abnormal wheel speed differences for each wheel is obtained and sorted to obtain the wheel abnormality sequence;

[0035] The vehicle's driving status is determined based on the abnormal wheel sequence, and the vehicle's driving status determination information is obtained.

[0036] Furthermore, the step of determining the vehicle driving state based on the wheel anomaly sequence to obtain vehicle driving state determination information includes:

[0037] Based on the wheel anomaly sequence, the wheel anomaly is located and labeled to obtain wheel anomaly labeling information;

[0038] The wheel anomaly labeling information is compared with the preset wheel target information to obtain wheel state comparison information;

[0039] The wheel driving state is determined based on the wheel state comparison information to obtain wheel driving state determination information.

[0040] The vehicle's driving status is determined based on the wheel driving status determination information to obtain the vehicle driving status determination information.

[0041] Furthermore, S3 includes:

[0042] Wheel braking is performed based on wheel braking control data to obtain wheel braking data;

[0043] The dynamic vehicle speed decay rate is obtained based on the wheel braking data.

[0044] The dynamic vehicle speed attenuation rate is compared with the preset dynamic vehicle speed attenuation threshold to obtain vehicle speed attenuation comparison information.

[0045] The wheel clamping force data is adjusted based on the vehicle speed decay comparison information to obtain clamping force adjustment data, and then vehicle speed adjustment data is obtained.

[0046] When the vehicle speed attenuation rate is greater than the preset vehicle speed attenuation threshold, the wheel clamping force data is adjusted to be reduced.

[0047] When the vehicle speed attenuation rate is less than or equal to the preset vehicle speed attenuation threshold, the wheel clamping force data is adjusted by increasing.

[0048] Further, S4 includes:

[0049] When the dynamic and static parking determination information is static parking, the vehicle speed is collected during static parking to obtain static vehicle speed data;

[0050] Static parking status analysis is performed based on static vehicle speed data to obtain static first parking status determination information;

[0051] The wheel status analysis command is triggered based on the static parking status determination information.

[0052] Perform static wheel state analysis according to the wheel state analysis command to obtain static second parking state determination information;

[0053] Static parking adjustment is determined by combining the static first parking status determination information with the static second parking status determination information, and static parking adjustment data is obtained.

[0054] Furthermore, the step of performing static parking state analysis based on static vehicle speed data to obtain static first parking state determination information includes:

[0055] The initial clamping force is obtained based on the static vehicle speed data, and static parking control is performed based on the initial clamping force to obtain static parking control data.

[0056] Obtain the static vehicle speed attenuation rate based on static parking control data;

[0057] The static vehicle speed attenuation rate is compared with a preset static vehicle speed attenuation threshold to obtain static attenuation comparison information.

[0058] Static parking status determination is performed based on the static attenuation comparison information to obtain static first parking status determination information.

[0059] Further, the step of performing static wheel state analysis according to the wheel state analysis command to obtain static second parking state determination information includes:

[0060] When a wheel status analysis command is received, wheel speed is collected for each wheel to obtain wheel speed data.

[0061] Obtain the maximum and minimum values ​​of all wheel speed data, and calculate the wheel speed deviation between the maximum and minimum values;

[0062] Anomaly risk assessment is performed based on the wheel speed deviation value to obtain anomaly risk assessment information.

[0063] Based on the abnormal risk assessment information, the static wheel status is determined to obtain the static second parking status assessment information.

[0064] Further, the step of determining static parking adjustment based on the static first parking state determination information and the static second parking state determination information to obtain static parking adjustment data includes:

[0065] Determine whether both the static first parking status determination information and the static second parking status determination information are abnormal to obtain status consistency determination information;

[0066] Based on the consistency judgment information, static parking compensation control is triggered to obtain the compensation clamping force;

[0067] Based on the compensation clamping force, static parking control is adjusted to obtain static parking adjustment data.

[0068] The beneficial effects of this invention are as follows:

[0069] By working in tandem with ESC and EPB, the limitations of single-system control are overcome, allowing braking control to better match the vehicle's actual dynamic and static driving conditions. Dual data support from vehicle speed and wheel speed avoids improper braking caused by errors in judging a single parameter, improving the stability and accuracy of EPB braking. Timely detection and handling of abnormal wheels effectively reduce the risk of braking imbalance, ensuring the vehicle's dynamic and static safety. Simultaneously, the dynamically optimized clamping force adjustment method makes speed control smoother. Attached Figure Description

[0070] Figure 1 This is a schematic diagram of a control method for an EPB product that combines vehicle speed and wheel speed. Detailed Implementation

[0071] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0072] In one embodiment of the present invention, a control method for an EPB product combining vehicle speed and wheel speed is proposed, the method comprising:

[0073] S1. Determine the vehicle's stability status through ESC, collect vehicle speed based on the vehicle stability status information, and then obtain dynamic and static parking judgment information. Trigger EPB control command based on the dynamic and static parking judgment information.

[0074] S2. Based on the dynamic and static parking judgment information and the EPB control command, analyze the vehicle speed status, generate clamping force data based on the vehicle speed analysis data, adjust the clamping force, obtain the wheel speed information during the adjustment process, judge abnormal wheels and generate wheel braking control data.

[0075] S3. Based on the wheel braking control data and the wheel speed attenuation rate, perform clamping force data adjustment analysis to obtain clamping force adjustment analysis data, and then obtain vehicle speed adjustment data.

[0076] S4. Dynamic and static parking judgment information: Analyze the vehicle speed and wheels for static parking, and adjust the static parking based on the vehicle speed analysis data and wheel analysis data to obtain static parking adjustment data.

[0077] The working principle and technical effects of the above solution are as follows: The Electronic Stability Program (ESC) dynamically triggers and precisely controls the parking brake by leveraging the vehicle's dynamic perception capabilities. The ESC determines the vehicle's real-time stability and collects vehicle speed data, using this as a basis to decide whether to perform dynamic emergency braking or static safe parking. Once EPB intervention is determined, the required initial clamping force is calculated based on real-time vehicle speed analysis and executed. During this process, the wheel speeds of all four wheels are continuously monitored, and a unique wheel speed difference sequence analysis method is used to accurately identify abnormal wheels that may experience dragging or slippage. The system incorporates vehicle speed decay rate as a feedback indicator to perform closed-loop adjustment of the clamping force, ensuring a smooth and efficient braking process until the vehicle reaches the target state.

[0078] This method achieves intelligent control throughout the entire process from perception and decision-making to execution, significantly improving the safety and adaptability of EPB products. It breaks through the limitations of traditional parking methods, which are only used for static parking, enabling it to serve as an effective braking backup system under dynamic conditions. By integrating ESC status, vehicle speed, and four-wheel wheel speed information, the system's judgment of vehicle status is more comprehensive and accurate. Its innovative abnormal wheel recognition algorithm effectively avoids vehicle instability caused by a single wheel dragging or insufficient braking force caused by a single wheel slipping during emergency braking, ensuring directional stability and braking efficiency during the braking process. Through closed-loop control based on vehicle speed decay rate, the application of braking force is made more linear and gentle.

[0079] In one embodiment of the present invention, S1 includes:

[0080] Obtain communication status information from ESC via EPB to obtain ESC status information;

[0081] Compare the ESC status information with the preset ESC status threshold; ESC status comparison information.

[0082] Based on the ESC status comparison information, the ESC status is determined to obtain the ESC status determination information.

[0083] Based on the ESC status determination information, vehicle speed is collected to obtain vehicle speed data.

[0084] When the ESC status determination information is unqualified, the vehicle speed is collected;

[0085] The vehicle speed data is compared with a preset vehicle speed threshold to obtain a vehicle speed comparison result.

[0086] Based on the vehicle speed comparison results, dynamic and static parking determination is performed to obtain dynamic and static parking determination information.

[0087] The EPB control command is triggered based on the dynamic and static parking determination information.

[0088] The working principle and technical effect of the above solution are as follows: The communication status of the ESC is used as the primary health indicator. Only when the ESC's own working status is abnormal (such as communication timeout or internal fault) and deemed unqualified, is the EPB control process initiated. This ensures that the EPB will not overstep its authority to intervene when the ESC is working normally. After confirming the need for intervention, the system directly collects the vehicle's longitudinal speed and compares it with a preset threshold (e.g., 5-7 km / h). If the speed is higher than the threshold, it is determined to be a dynamic parking scenario, meaning the vehicle needs to be forcibly braked while in motion; if the speed is lower than the threshold, it is determined to be a static parking scenario, with the goal of keeping or achieving vehicle stillness. This clear judgment logic forms the basis for all subsequent differentiated control strategies.

[0089] This method establishes an intelligent triggering mechanism with ESC status as a prerequisite, creating a clear hierarchy in system collaboration and improving the coordination and reliability of the entire vehicle's electronic systems. It achieves precise timing of control and intelligent scenario recognition. By comparing hard state thresholds, the possibility of false triggering is avoided, ensuring the seriousness and necessity of EPB control commands. Simultaneously, dynamic and static determinations based on vehicle speed provide a decisive basis for the system to execute drastically different control strategies, enabling the same system to flexibly handle different needs from high-speed emergency braking to low-speed parking, greatly expanding the functional boundaries and application value of EPB.

[0090] In one embodiment of the present invention, S2 includes:

[0091] When the EPB receives the EPB control command and the dynamic and static parking judgment information is dynamic parking, it collects the vehicle's longitudinal speed to obtain dynamic speed data.

[0092] Based on the dynamic vehicle speed data, the vehicle speed status is determined to obtain vehicle speed status determination information.

[0093] Based on the vehicle speed status determination information, corresponding clamping force data is generated, and dynamic vehicle speed data adjustment is performed.

[0094] Obtain the wheel speed difference data between each wheel of the vehicle and other wheels, and obtain three wheel speed difference data for each wheel;

[0095] The wheel speed difference data of the three wheels of each wheel are analyzed to determine the vehicle driving status and obtain vehicle driving status judgment information.

[0096] Wheel braking control data is generated based on the vehicle driving status judgment information.

[0097] When the vehicle driving status determination information indicates an abnormal driving status, wheel braking control data is generated based on the wheel status comparison information.

[0098] When the vehicle driving status determination information is normal driving status, wheel monitoring weight information is generated based on wheel status comparison information, wheel status weight monitoring is performed, and wheel status monitoring information is obtained.

[0099] The working principle and technical effect of the above technical solution are as follows: When the system enters dynamic parking mode, the control process is divided into two parallel main lines: the vehicle speed main line and the wheel speed main line. On the vehicle speed main line, the system maps the current vehicle speed to the corresponding target clamping force based on real-time collected dynamic vehicle speed data and through an internally pre-calibrated algorithm (such as lookup table method or PID control). The EPB actuator applies braking force accordingly, aiming to adjust the vehicle speed to decrease as expected. On the wheel speed main line, the system performs refined wheel status monitoring. It calculates the wheel speed difference between each wheel and the other three wheels, thus generating three difference values ​​for each wheel. By deeply analyzing these wheel speed difference data, it is possible to identify whether the vehicle's driving posture is normal. For example, if multiple wheel speed differences of a certain wheel are abnormally large, it indicates that the wheel may be locked or suspended in the air.

[0100] This solution achieves unified management of both macroscopic braking effect and microscopic wheel status through dual-mainline parallel control. Its core effect lies in upgrading the traditional one-size-fits-all braking method to intelligent braking that observes individual wheel movements. The system not only focuses on whether the vehicle as a whole slows down, but also on how each wheel slows down. This anomaly detection mechanism based on multi-wheel speed differences can identify potentially risky wheels very early, allowing for targeted adjustments before the vehicle experiences instability such as fishtailing or veering. By distinguishing between normal and abnormal states and generating different control or monitoring commands, the system lays a solid foundation for differentiated braking force distribution, ensuring directional stability and vehicle attitude controllability during dynamic braking.

[0101] In one embodiment of the present invention, the step of performing wheel speed difference analysis on the three wheel speed difference data of each wheel, and then determining the vehicle driving state to obtain vehicle driving state determination information, includes:

[0102] Sort the three wheel speed difference data for each wheel to obtain the first wheel speed difference sequence;

[0103] Obtain all first-round speed difference sequences for all wheels, and based on all first-round speed difference sequences, obtain the wheel speed difference of the first-ranked wheel for each wheel;

[0104] Sort the wheel speed differences of the first-ranked wheels among multiple wheels to obtain the second wheel speed difference sequence;

[0105] Obtain the speed difference interval data between adjacent wheels based on the second round speed difference sequence;

[0106] The adjacent wheel speed difference interval data is compared with a preset wheel speed difference interval threshold to obtain the wheel speed difference interval comparison result;

[0107] Based on the wheel speed difference interval comparison result, the second wheel speed difference sequence is broken, and the wheel speed difference of the wheel that is sorted first after the break is obtained and determined to be an abnormal wheel speed difference.

[0108] The number of abnormal wheel speed differences for each wheel is obtained and sorted to obtain the wheel abnormality sequence;

[0109] The vehicle's driving status is determined based on the abnormal wheel sequence, and the vehicle's driving status determination information is obtained.

[0110] The working principle and technical effect of the above solution are as follows: For each wheel, the three wheel speed differences are sorted, and the largest difference value is selected, representing the degree of incompatibility between that wheel and the other wheels. Then, these largest difference values ​​of all wheels are collected to form a new sequence and sorted again. The key to the algorithm is finding natural breaks in this new sequence. By calculating the interval between adjacent values ​​and comparing it with a preset threshold, a clear dividing point is found. Those largest difference values ​​located before the dividing point, i.e., those significantly larger than other members, are judged as abnormal wheel speed differences. The number of times each wheel appears on the list is counted to form an abnormal wheel sequence, thereby identifying the wheel with the highest probability of failure.

[0111] The technical advantage of this method lies in its strong anti-interference capability and accurate anomaly identification ability. Traditional fixed threshold methods are prone to false alarms under complex conditions such as vehicle turning or bumpy driving. This method, however, employs a strategy of relative comparison and finding discontinuities in data clusters, allowing the judgment criteria to adapt to the current real-time wheel speed environment, significantly reducing the risk of misjudgment. It effectively filters out uniform wheel speed fluctuations caused by uneven road surfaces and normal turning, while extracting truly incongruous and atypical abnormal wheel speed signals. This intelligent filtering mechanism provides high-quality, highly reliable fault diagnosis information for the vehicle stability system, a crucial prerequisite for achieving advanced vehicle stability control.

[0112] In one embodiment of the present invention, the step of determining the vehicle driving state based on the wheel anomaly sequence to obtain vehicle driving state determination information includes:

[0113] Based on the wheel anomaly sequence, the wheel anomaly is located and labeled to obtain wheel anomaly labeling information;

[0114] The wheel anomaly labeling information is compared with the preset wheel target information to obtain wheel state comparison information;

[0115] The wheel driving state is determined based on the wheel state comparison information to obtain wheel driving state determination information.

[0116] The vehicle's driving status is determined based on the wheel driving status determination information to obtain the vehicle driving status determination information.

[0117] The working principle and technical effect of the above technical solution are as follows: After obtaining the wheel anomaly sequence, this step is responsible for converting the data into specific vehicle state diagnosis. The system locates and labels specific wheels based on the anomaly sequence; for example, the left front wheel is labeled as a level one anomaly risk and the right rear wheel as a level two anomaly risk. The system compares this real-time labeling information with preset wheel target information. This preset information includes wheel anomaly characteristic models of the vehicle under different instability modes; for example, a single-sided wheel anomaly may indicate a low-traction road surface on one side, and a diagonal wheel anomaly may indicate the vehicle body lifting up. Through comparison, the system matches the current wheel state with known fault or risk modes, thereby first determining the driving state of each wheel, and then combining the determination results of all wheels to make a final decision on the overall vehicle driving state.

[0118] This method achieves a semantic elevation from low-level data to high-level decision-making. It goes beyond simply identifying which wheel is malfunctioning; it explains the dangerous situation the problem pattern implies for the entire vehicle. This pattern-matching-based decision-making method significantly enhances the system's ability to understand complex vehicle dynamics. This allows the EPB control system to move beyond mechanically executing braking commands and instead perceive the vehicle's attitude and trends, much like an experienced driver. This deep state awareness provides crucial information for developing the most appropriate control strategy, enabling the control system to address the specific problem rather than applying blind force, thus achieving greater precision and effectiveness in rescuing vehicles in critical situations.

[0119] In one embodiment of the present invention, S3 includes:

[0120] Wheel braking is performed based on wheel braking control data to obtain wheel braking data;

[0121] The dynamic vehicle speed decay rate is obtained based on the wheel braking data.

[0122] The dynamic vehicle speed attenuation rate is compared with the preset dynamic vehicle speed attenuation threshold to obtain vehicle speed attenuation comparison information.

[0123] The wheel clamping force data is adjusted based on the vehicle speed decay comparison information to obtain clamping force adjustment data, and then vehicle speed adjustment data is obtained.

[0124] When the vehicle speed attenuation rate is greater than the preset vehicle speed attenuation threshold, the wheel clamping force data is adjusted to be reduced.

[0125] When the vehicle speed attenuation rate is less than or equal to the preset vehicle speed attenuation threshold, the wheel clamping force data is adjusted by increasing.

[0126] The working principle and technical effect of the above technical solution are as follows: Braking is executed based on the wheel braking control data generated in the preceding steps, and during this process, the dynamic vehicle speed decay rate, i.e., the rate at which the vehicle speed decreases per unit time, is continuously calculated. This decay rate is compared with a preset, ideal dynamic vehicle speed decay threshold. This threshold typically represents an optimal deceleration range that ensures efficient braking while also considering vehicle stability and passenger comfort. The comparison result generates crucial vehicle speed decay comparison information: if the actual decay rate is too fast (greater than the threshold), it indicates excessive braking force, posing a risk of wheel lock-up or passenger discomfort, and the system will instruct a reduction in clamping force; if the decay rate is too slow (less than or equal to the threshold), it indicates insufficient braking force and excessive braking distance, and the system will instruct an increase in clamping force.

[0127] This method introduces vehicle speed decay rate as the core feedback indicator to achieve adaptive closed-loop adjustment of clamping force. Its core effect is to achieve a more refined and humanized braking process. It completely changes the constant output characteristic of traditional braking systems, allowing braking force to be dynamically adjusted according to actual braking performance. This not only ensures that the maximum friction force of the ground is utilized for braking under any adhesion conditions, shortening the braking distance, but more importantly, it fundamentally maintains the vehicle's steering ability and stability by preventing wheel lock-up caused by excessive braking. Simultaneously, by controlling deceleration within a reasonable range, it avoids passenger discomfort and vehicle impact caused by excessive braking, significantly improving the vehicle's ride quality and comfort while ensuring safety.

[0128] In one embodiment of the present invention, S4 includes:

[0129] When the dynamic and static parking determination information is static parking, the vehicle speed is collected during static parking to obtain static vehicle speed data;

[0130] Static parking status analysis is performed based on static vehicle speed data to obtain static first parking status determination information;

[0131] The wheel status analysis command is triggered based on the static parking status determination information.

[0132] Perform static wheel state analysis according to the wheel state analysis command to obtain static second parking state determination information;

[0133] Static parking adjustment is determined by combining the static first parking status determination information with the static second parking status determination information, and static parking adjustment data is obtained.

[0134] The working principle and technical effects of the above technical solution are as follows: This embodiment is the top-level logical framework for static parking control, the core of which lies in the adoption of a dual-confirmation safety strategy. When the system is determined to be in a static parking scenario, the control process is divided into two parallel analysis paths. The first path is the vehicle speed analysis path: the system continuously collects static vehicle speed data and analyzes the macroscopic static state of the vehicle based on this, generating static first parking state determination information. The second path is the wheel speed analysis path: after receiving the analysis command, the system simultaneously performs microscopic monitoring of the wheel speeds of the four wheels, and by analyzing the consistency between the wheel speeds, it determines whether there is a risk of instability in individual wheels of the vehicle, thereby generating static second parking state determination information. Finally, a central decision-making unit integrates the determination results from both aspects, and only when the information from both dimensions points to the need for intervention will the final static parking adjustment command be generated.

[0135] By fusing multi-dimensional information, the reliability and safety of static parking determination are greatly improved. Traditional static parking methods may only focus on whether the vehicle is stationary, while this method simultaneously considers whether the vehicle is stable and whether each wheel is reliably positioned. This dual-modal determination mechanism effectively avoids misjudgments. For example, on uneven roads or when one wheel of the vehicle is off-center, the vehicle speed sensor alone may determine that the vehicle is stationary, but wheel speed analysis can detect abnormal wheel speed differences, thus identifying potential risks of vehicle rollover. Conversely, when parking after a normal turn, there may be brief and slight differences in wheel speed, but vehicle speed analysis can confirm that the vehicle as a whole has come to a standstill, preventing the system from overreacting. This cross-validation mechanism ensures that the activation of static parking control is both timely and accurate, fundamentally improving parking safety redundancy.

[0136] In one embodiment of the present invention, the step of performing static parking state analysis based on static vehicle speed data to obtain static first parking state determination information includes:

[0137] The initial clamping force is obtained based on the static vehicle speed data, and static parking control is performed based on the initial clamping force to obtain static parking control data.

[0138] Obtain the static vehicle speed attenuation rate based on static parking control data;

[0139] The static vehicle speed attenuation rate is compared with a preset static vehicle speed attenuation threshold to obtain static attenuation comparison information.

[0140] Static parking status determination is performed based on the static attenuation comparison information to obtain static first parking status determination information.

[0141] The working principle and technical effect of the above solution are as follows: In a static parking scenario, the system does not simply apply a fixed clamping force, but executes a dynamic, predictive force control cycle. First, the system calculates and applies an initial clamping force based on the initial static vehicle speed. This force is typically set to a moderate level sufficient to stabilize the vehicle. The system then enters a monitoring phase, where the key analytical indicator is the static speed decay rate, i.e., the smoothness and efficiency of the process of the vehicle decreasing from a very low creep speed to a complete stop. The system compares this actual decay rate with a preset ideal threshold. If the decay is too slow, it indicates that the initial clamping force is insufficient, and the vehicle may fail to stop or respond slowly; if the decay process meets or exceeds expectations, it indicates that the current clamping force is effective. Based on this comparison result, the system makes an initial determination of the current parking state (stable or unstable).

[0142] The technical advantage of this solution lies in optimizing static parking from a simple on / off action into an intelligent force control process. By monitoring the vehicle speed decay rate, the system can quickly assess and diagnose the effectiveness of parking in its initial stages. This not only ensures that the vehicle can be brought to a quick and smooth stop under various inclines or loads, avoiding nose-diving or brief roll-back due to insufficient initial braking force, but also greatly improves parking comfort and immediate safety. More importantly, it establishes a performance feedback-based evaluation mechanism, providing crucial decision-making basis for whether force compensation is needed. This enables the EPB system to possess self-sensing and self-evaluation capabilities during static parking, achieving a leap from passive execution to active control.

[0143] In one embodiment of the present invention, the step of performing static wheel state analysis according to wheel state analysis instructions to obtain static second parking state determination information includes:

[0144] When a wheel status analysis command is received, wheel speed is collected for each wheel to obtain wheel speed data.

[0145] Obtain the maximum and minimum values ​​of all wheel speed data, and calculate the wheel speed deviation between the maximum and minimum values;

[0146] Anomaly risk assessment is performed based on the wheel speed deviation value to obtain anomaly risk assessment information.

[0147] Based on the abnormal risk assessment information, the static wheel status is determined to obtain the static second parking status assessment information.

[0148] The working principle and technical effect of the above-mentioned technical solution are as follows: During static parking, the system activates synchronous high-precision monitoring of the wheel speeds of all wheels. The system acquires the wheel speeds of all four wheels in real time, identifies the maximum and minimum values, and calculates the wheel speed deviation between them. This deviation becomes a key indicator for measuring the consistency of the behavior of the four wheels. In an ideal, completely stationary state, this value should be zero. If a deviation occurs, the system compares this deviation value with a preset safety tolerance to determine any abnormal risks. For example, a deviation value significantly greater than zero may mean that one wheel is slipping on ice or is slipping due to poor brake pad contact, while the other wheels are locked. Based on this, the system generates secondary parking state determination information regarding the stability of the wheels themselves.

[0149] This method adds a crucial microscopic monitoring layer to static parking safety. It effectively identifies localized risks that traditional vehicle speed sensors cannot detect. In complex road conditions, such as when a vehicle is parked on icy, slippery, or soft surfaces, some wheels may have good traction while others have extremely poor traction. This method, through wheel speed deviation analysis, can sensitively detect this limp state and issue timely risk warnings. This allows the system to recognize that although the vehicle appears stationary, its parking state is vulnerable, and it is highly susceptible to instability once disturbed by external forces (such as the gravity component of a slope or a collision). This early detection capability of potential risks is a core technological guarantee for achieving high-level parking safety, especially preventing slope rollback and accidental movement.

[0150] In one embodiment of the present invention, the step of determining static parking adjustment based on static first parking state determination information and static second parking state determination information to obtain static parking adjustment data includes:

[0151] Determine whether both the static first parking status determination information and the static second parking status determination information are abnormal to obtain status consistency determination information;

[0152] Based on the consistency judgment information, static parking compensation control is triggered to obtain the compensation clamping force;

[0153] Based on the compensation clamping force, static parking control is adjusted to obtain static parking adjustment data.

[0154] The working principle and technical effect of the above solution are as follows: It receives the judgment results from two paths—vehicle speed analysis and wheel speed analysis (first and second parking state judgment information)—and performs a consistency judgment on them. The most critical situation is when both paths determine the state as abnormal. This constitutes a high-confidence risk signal, indicating that the vehicle not only has insufficient overall parking efficiency (first information abnormality) but also a local risk of instability in individual wheels (second information abnormality). At this time, the system will decisively trigger the static parking compensation control mechanism. The core of this mechanism is to calculate and output an additional compensation clamping force, which is superimposed on the initial clamping force to strengthen the actuator adjustment, thereby completely eliminating the identified risk.

[0155] This method achieves precise and robust protection for static parking control. Through information fusion decision-making, it avoids excessive system intervention or frequent actions caused by accidental misjudgments due to a single path, ensuring system robustness. When a real risk is confirmed, it can decisively activate the compensation mechanism, providing a decisive increase in braking force. This design allows the system to handle extreme conditions such as parking on steep inclines or with one wheel on a low-traction surface, ensuring the vehicle is firmly locked under various adverse conditions. This mechanism elevates static parking from a potentially reliable state to a proactively ensured safety state, providing drivers with the ultimate experience of absolute peace of mind after letting go, greatly enhancing user trust and safety value of EPB products.

[0156] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A control method for an EPB product that combines vehicle speed and wheel speed, characterized in that, The method includes: S1. Determine the vehicle's stability status through ESC, collect vehicle speed based on the vehicle stability status information, and then obtain dynamic and static parking judgment information. Trigger EPB control command based on the dynamic and static parking judgment information. S2. Based on the dynamic and static parking judgment information and the EPB control command, analyze the vehicle speed status, generate clamping force data based on the vehicle speed analysis data, adjust the clamping force, obtain the wheel speed information during the adjustment process, judge abnormal wheels and generate wheel braking control data. S3. Based on the wheel braking control data and the wheel speed attenuation rate, perform clamping force data adjustment analysis to obtain clamping force adjustment analysis data, and then obtain vehicle speed adjustment data. S4. Based on the dynamic and static parking judgment information, perform static parking speed and wheel analysis, and adjust the static parking according to the speed analysis data and wheel analysis data to obtain static parking adjustment data. Wherein, S1 includes: Obtain communication status information from ESC via EPB; The ESC status information is compared with the preset ESC status threshold to obtain ESC status comparison information. Based on the ESC status comparison information, the ESC status is determined to obtain the ESC status determination information. Vehicle speed is collected based on the ESC status determination information to obtain vehicle speed data. The vehicle speed data is compared with a preset vehicle speed threshold to obtain a vehicle speed comparison result. Based on the vehicle speed comparison results, dynamic and static parking determination is performed to obtain dynamic and static parking determination information. The EPB control command is triggered based on the dynamic and static parking determination information. Wherein, S2 includes: When the EPB receives the EPB control command and the dynamic and static parking judgment information is dynamic parking, it collects the vehicle's longitudinal speed to obtain dynamic speed data. Based on the dynamic vehicle speed data, the vehicle speed status is determined to obtain vehicle speed status determination information. Based on the vehicle speed status determination information, corresponding clamping force data is generated, and dynamic vehicle speed data adjustment is performed. Obtain the wheel speed difference data between each wheel of the vehicle and other wheels, and obtain three wheel speed difference data for each wheel; The wheel speed difference data of the three wheels of each wheel are analyzed to determine the vehicle driving status and obtain vehicle driving status judgment information. Wheel braking control data is generated based on the vehicle driving status judgment information; The process of analyzing the wheel speed difference data of the three wheel speeds for each wheel to determine the vehicle's driving state and obtain vehicle driving state determination information includes: Sort the three wheel speed difference data for each wheel to obtain the first wheel speed difference sequence; Obtain all first-round speed difference sequences for all wheels, and based on all first-round speed difference sequences, obtain the wheel speed difference of the first-ranked wheel for each wheel; Sort the wheel speed differences of the first-ranked wheels among multiple wheels to obtain the second wheel speed difference sequence; Obtain the speed difference interval data between adjacent wheels based on the second round speed difference sequence; The adjacent wheel speed difference interval data is compared with a preset wheel speed difference interval threshold to obtain the wheel speed difference interval comparison result; Based on the wheel speed difference interval comparison result, the second wheel speed difference sequence is broken, and the wheel speed difference of the wheel that is sorted first after the break is obtained and determined to be an abnormal wheel speed difference. The number of abnormal wheel speed differences for each wheel is obtained and sorted to obtain the wheel abnormality sequence; The vehicle's driving status is determined based on the abnormal wheel sequence, and the vehicle's driving status information is obtained.

2. The control method for an EPB product combining vehicle speed and wheel speed according to claim 1, characterized in that, The process of determining the vehicle's driving status based on the wheel anomaly sequence to obtain vehicle driving status determination information includes: Based on the wheel anomaly sequence, the wheel anomaly is located and labeled to obtain wheel anomaly labeling information; The wheel anomaly labeling information is compared with the preset wheel target information to obtain wheel state comparison information; The wheel driving state is determined based on the wheel state comparison information to obtain wheel driving state determination information. The vehicle's driving status is determined based on the wheel driving status determination information to obtain the vehicle driving status determination information.

3. The control method for an EPB product combining vehicle speed and wheel speed according to claim 1, characterized in that, S3 includes: Wheel braking is performed based on wheel braking control data to obtain wheel braking data; The dynamic vehicle speed decay rate is obtained based on the wheel braking data. The dynamic vehicle speed attenuation rate is compared with the preset dynamic vehicle speed attenuation threshold to obtain vehicle speed attenuation comparison information. The wheel clamping force data is adjusted based on the vehicle speed decay comparison information to obtain clamping force adjustment data, and then vehicle speed adjustment data is obtained.

4. The control method for an EPB product combining vehicle speed and wheel speed according to claim 1, characterized in that, S4 includes: When the dynamic and static parking determination information is static parking, the vehicle speed is collected during static parking to obtain static vehicle speed data; Static parking status analysis is performed based on static vehicle speed data to obtain static first parking status determination information; The wheel status analysis command is triggered based on the static first parking status determination information. Perform static wheel state analysis according to the wheel state analysis command to obtain static second parking state determination information; Static parking adjustment is determined by combining the static first parking status determination information with the static second parking status determination information, and static parking adjustment data is obtained.

5. The control method for an EPB product combining vehicle speed and wheel speed according to claim 4, characterized in that, The step of performing static parking state analysis based on static vehicle speed data to obtain static first parking state determination information includes: The initial clamping force is obtained based on the static vehicle speed data, and static parking control is performed based on the initial clamping force to obtain static parking control data. Obtain the static vehicle speed attenuation rate based on static parking control data; The static vehicle speed attenuation rate is compared with a preset static vehicle speed attenuation threshold to obtain static attenuation comparison information. Static parking status determination is performed based on the static attenuation comparison information to obtain static first parking status determination information.

6. The control method for an EPB product combining vehicle speed and wheel speed according to claim 5, characterized in that, The step of performing static wheel state analysis according to the wheel state analysis command to obtain static second parking state determination information includes: When a wheel status analysis command is received, wheel speed is collected for each wheel to obtain wheel speed data. Obtain the maximum and minimum values ​​of all wheel speed data, and calculate the wheel speed deviation between the maximum and minimum values; Anomaly risk assessment is performed based on the wheel speed deviation value to obtain anomaly risk assessment information. Based on the abnormal risk assessment information, the static wheel status is determined to obtain the static second parking status assessment information.

7. The control method for an EPB product combining vehicle speed and wheel speed according to claim 4, characterized in that, The step of determining static parking adjustment based on the static first parking state determination information and the static second parking state determination information to obtain static parking adjustment data includes: Determine whether both the static first parking status determination information and the static second parking status determination information are abnormal to obtain status consistency determination information; Based on the consistency judgment information, static parking compensation control is triggered to obtain the compensation clamping force; Based on the compensation clamping force, static parking control is adjusted to obtain static parking adjustment data.

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