Statistical method of vehicle sliding data, computer program product, vehicle-mounted controller and medium

Abstract

The invention relates to the field of electrical digital, in particular to a statistical method of vehicle sliding data, a computer program product, a vehicle-mounted controller and a medium. The vehicle sliding data statistical method comprises the steps that the current state of a vehicle is collected, wherein the current state comprises the current vehicle speed, the current engine rotating speed, the current accelerator opening degree and the current gear; determining a rotating speed threshold value according to the historical average engine rotating speed; determining a vehicle speed threshold value according to the gradient of the road section where the vehicle is located; if the current vehicle speed is larger than the vehicle speed threshold value, the current engine rotating speed is smaller than the rotating speed threshold value, the current accelerator opening degree is smaller than or equal to 0, and the current gear is a neutral gear, it is determined that the vehicle is in a sliding state; and counting target data of the vehicle in the sliding state. The sliding state can be identified more accurately, the possibility of misjudgment is reduced, and the accuracy of sliding data statistics is improved.

Description

Technical Field

[0001] The present application relates to the field of electronic digital processing technology, and in particular to a statistical method for vehicle coasting data, a computer program product, a vehicle-mounted controller, and a medium. Background Art

[0002] Vehicles generate a wide variety of data, and with the development of intelligent and connected technologies, the amount of data is growing exponentially. This data is collected through channels such as on-board sensors, vehicle networking systems, and external infrastructure, and can be applied in multiple fields after analysis.

[0003] Coasting data is a crucial component of vehicle data analysis, used to detect and analyze driver coasting behavior. Existing technologies typically rely on a single signal (e.g., throttle opening = 0) to determine coasting status and generate statistical data. However, this single-signal approach can easily lead to misjudgment of coasting status, compromising data processing accuracy.

[0004] In view of this, this application is filed. Summary of the Invention

[0005] The purpose of this application is to provide a vehicle coasting data statistics method, computer program product, vehicle-mounted controller and medium to accurately identify the vehicle's coasting state and count the coasting data.

[0006] In order to achieve the above objectives, this application adopts the following technical solutions: In a first aspect, the present application provides a statistical method for vehicle coasting data, comprising: Collecting the current state of the vehicle, including the current vehicle speed, current engine speed, current throttle opening, and current gear position; determining a speed threshold based on historical average engine speed; determining a vehicle speed threshold according to the slope of the road section where the vehicle is located; If the current vehicle speed is greater than the vehicle speed threshold, the current engine speed is less than the speed threshold, the current throttle opening is less than or equal to 0, and the current gear is neutral, determining that the vehicle is in a coasting state; Counting target data of the vehicle in a coasting state; the target data includes at least one of coasting mileage, coasting time, and coasting fuel consumption.

[0007] In a second aspect, the present application provides a computer program product, which, when executed on a computer, enables the computer to execute the vehicle coasting data statistics method described in the first aspect.

[0008] In a third aspect, the present application provides a vehicle-mounted controller, comprising: at least one processor, and a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by at least one of the processors, and the instructions are executed by at least one of the processors to enable the at least one processor to execute the above-mentioned vehicle glide data statistical method.

[0009] In a fourth aspect, the present application provides a computer-readable storage medium having computer instructions stored thereon, wherein the computer instructions are used to enable a computer to execute the above-mentioned vehicle glide data statistical method.

[0010] Compared with the prior art, the present invention has the following advantages: This application collects the vehicle's current speed, engine speed, throttle position, and gear position, and uses this multi-dimensional data to comprehensively determine whether the vehicle is coasting. Compared to existing solutions that determine coasting status based solely on a single signal, this method can more accurately identify coasting status, reduce the possibility of misjudgment, and improve the accuracy of coasting data statistics, providing accurate data support for driving behavior analysis and safety warnings. Furthermore, this application determines a speed threshold based on historical average engine speed and a speed threshold based on the slope of the road section the vehicle is on. This threshold is then compared with the corresponding engine speed and speed, taking into account the impact of vehicle engine performance on engine speed and the impact of road slope on vehicle speed, effectively improving the accuracy of coasting status judgment. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the specific implementation methods or the description of the prior art. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0012] Figure 1 This is a flow chart of a statistical method for vehicle coasting data provided by this application; Figure 2 1 is a flow chart of another method for collecting vehicle coasting data provided by an embodiment of the present application; Figure 3 This is a schematic diagram of a method for calculating accumulated mileage provided in an embodiment of the present application; Figure 4 This is a schematic diagram of a method for calculating cumulative fuel consumption provided in an embodiment of the present application; Figure 5 This is a flowchart of another method for collecting vehicle coasting data provided by an embodiment of the present application; Figure 6It is a structural diagram of the electronic device provided in this application. DETAILED DESCRIPTION

[0013] The following description of exemplary embodiments of the present application is made in conjunction with the accompanying drawings, including various details of the embodiments of the present application to facilitate understanding. These details should be considered as merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present application. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0014] The present application is further described in detail below with reference to the embodiments.

[0015] Figure 1 This is a flow chart of a vehicle coasting data statistics method provided by this embodiment. This method can be executed by a computer program and integrated into a vehicle controller, which can be an electronic control unit (ECU) or a vehicle communication module (Telematics box, T-box). This embodiment uses the vehicle coasting data statistics method integrated into the ECU or T-box to identify the vehicle's coasting state in real time and to collect real-time statistics of the vehicle's coasting state data. Figure 1 As shown, this embodiment provides a method for collecting vehicle coasting data, comprising the following steps: S110 , collecting the current state of the vehicle, where the current state includes the current vehicle speed, the current engine speed, the current throttle opening, and the current gear position.

[0016] Real-time collection of the vehicle's current status, including current vehicle speed, current engine speed, current throttle opening and current gear.

[0017] The vehicle controller uses the ECU to collect the aforementioned current status. For example, the instrument panel ECU collects the current vehicle speed, the engine ECU collects the current engine speed and throttle position, and the transmission ECU collects the current gear position. Each ECU shares data with the vehicle controller via the Controller Area Network (CAN) bus, following the CAN protocol. For example, a CAN signal of 0x01 indicates P gear, 0x02 indicates R gear, 0x03 indicates N gear, and 0x04 indicates D gear.

[0018] This application only needs to interact with each ECU, obtain some of the required CAN signals for parsing to get the current status, and does not need to obtain the full amount of CAN signals, which reduces the amount of data processing.

[0019] S120: Determine a speed threshold according to a historical average engine speed.

[0020] The historical average engine speed is the average of the engine speeds at each moment in the historical period before the current moment, and can reflect the engine performance of the vehicle, so that corresponding speed thresholds are set for different engine performances.

[0021] S130. Determine a vehicle speed threshold according to the slope of the road section where the vehicle is located.

[0022] If a vehicle is traveling on a flat road, assume the coasting speed is A. If the vehicle is traveling uphill, the coasting speed will be less than A due to resistance. If the vehicle is traveling downhill, the coasting speed will be greater than A due to inertia. This embodiment considers the impact of road slope on coasting speed and sets corresponding speed thresholds. The angle between the vehicle's direction of travel and the horizontal plane is defined as the slope. A positive slope indicates an uphill slope, while a negative slope indicates a downhill slope. For example, the uphill speed threshold is lower than the downhill speed threshold.

[0023] S140: If the current vehicle speed is greater than the vehicle speed threshold, the current engine speed is less than the speed threshold, the current throttle opening is less than or equal to 0, and the current gear is neutral, it is determined that the vehicle is in a coasting state.

[0024] When the current throttle opening is 0% (fully released), the gear should be in neutral, and the vehicle may be coasting, indicating that the driver has no intention of accelerating. When the vehicle is coasting, wind resistance and rolling resistance affect the vehicle's speed, preventing it from reaching high speeds. The current engine speed reflects the state of the transmission system. This embodiment comprehensively considers the current vehicle speed, engine speed, throttle opening, and gear position to determine whether the vehicle is coasting, thus avoiding misjudgments.

[0025] The vehicle is determined to be coasting if the current vehicle speed is less than the speed threshold, the current engine speed is less than the speed threshold, the current throttle opening is less than or equal to 0, and the current gear is neutral. Four conditions are defined for determining whether the vehicle is coasting. If all four conditions are met, the vehicle is considered to be coasting.

[0026] If the current vehicle speed is greater than or equal to the vehicle speed threshold, or the current engine speed is greater than or equal to the speed threshold, the current throttle opening is greater than 0, or the current gear is not neutral, the vehicle is not in a coasting state and the process returns to continue collecting the vehicle's current state.

[0027] S150: Count target data of the vehicle in the coasting state.

[0028] While the vehicle is coasting, data generated by the vehicle is collected. To distinguish it from data in non-coasting states, the collected coasting data is referred to as target data. The target data includes at least one of coasting mileage, coasting time, and coasting fuel consumption. Coasting mileage is the total mileage (unit: km) of the vehicle in coasting mode, coasting time is the total time (unit: seconds) of the vehicle in coasting mode, and coasting fuel consumption is the total fuel consumption (unit: L) of the vehicle in coasting mode. This embodiment does not limit the collection method; it may be an averaging method, an accumulation method, or the like.

[0029] This application collects the vehicle's current speed, engine speed, throttle position, and gear position, and uses this multi-dimensional data to comprehensively determine whether the vehicle is coasting. Compared to existing solutions that determine coasting status based solely on a single signal, this method can more accurately identify coasting status, reduce the possibility of misjudgment, and improve the accuracy of coasting data statistics, providing accurate data support for driving behavior analysis and safety warnings. Furthermore, this application determines a speed threshold based on historical average engine speed and a speed threshold based on the slope of the road section the vehicle is on. This threshold is then compared with the corresponding engine speed and speed, taking into account the impact of vehicle engine performance on engine speed and the impact of road slope on vehicle speed, effectively improving the accuracy of coasting status judgment.

[0030] Figure 2 This is a flowchart of another statistical method for vehicle coasting data provided in an embodiment of the present application, which refines the rotation speed threshold and vehicle speed threshold and lists the uses of the target data. Figure 2 The methods provided include: S210 , collecting the current state of the vehicle, which includes the current vehicle speed s1 , the current engine speed e_rpm, the current throttle opening p and the current gear position d.

[0031] Define the current gear position d as 0 for parking, d as 1 for driving, d as 2 for neutral, and d as 3 for reverse.

[0032] S220: Calculate the difference between the historical average engine speed and the coasting reference speed; and obtain a speed threshold value based on the coasting reference speed, the difference, and a first set adjustment coefficient.

[0033] Calculate the average value of the engine speed e_rpm1 over the last N moments, where N can be 10. Use the following formula to calculate the speed threshold e_rpm_threshold_dynamic: e_rpm_threshold_dynamic=e_rpm2 + k1 * (e_rpm1 -e_rpm2 ); Formula (1) e_rpm2 is the reference speed for coasting in neutral, also known as the coasting reference speed, for example, 800 rpm. k1 is the first set adjustment coefficient, which controls the deviation of the speed threshold from the coasting reference speed. If the historical average engine speed is below 800, the speed threshold is lowered; otherwise, it is raised.

[0034] S230 , collecting the slope of the vehicle's current position in real time, and averaging the slopes of various positions on the road section where the vehicle is located to obtain an average slope.

[0035] Optionally, the slope of the vehicle's current position is collected in real time by an on-board gyroscope or inertial measurement unit, or the vehicle position is collected by a vehicle positioning device and combined with the slope marked in the high-precision map to obtain the slope of the vehicle's current position (in degrees).

[0036] S240: Normalize the average slope to obtain a slope coefficient pd.

[0037] The average slope reflects the overall condition of the current road section. The average slope can be divided by 90 degrees to obtain the slope coefficient, which is converted into a scalar.

[0038] S250: Obtain a vehicle speed threshold value according to the coasting reference vehicle speed, the slope coefficient, and the second set adjustment coefficient.

[0039] The speed threshold s_threshold_dynamic is calculated using the following formula: s_threshold_dynamic = s_1 - k2 × pd; Formula (2) Where s_1 is the reference speed for coasting in neutral, also known as the coasting reference speed, for example, 20 km / h. k2 is the second set adjustment coefficient, which is used to convert the slope coefficient into a speed adjustment. When the road is uphill (positive slope coefficient), it is recommended to lower the speed threshold; when the road is downhill (negative slope coefficient), the speed threshold can be appropriately increased.

[0040] S260. Smoothing the current vehicle speed based on the vehicle speed at the previous moment to obtain the smoothed current vehicle speed; smoothing the current engine speed based on the engine speed at the previous moment to obtain the smoothed current engine speed; smoothing the current throttle opening based on the throttle opening at the previous moment to obtain the smoothed current throttle opening.

[0041] Considering that there is noise in the current vehicle speed, current engine speed and current throttle opening, which will affect the judgment of the coasting state, a filter is used to filter the current vehicle speed, current engine speed and current throttle opening.

[0042] In this step, the following formula is used for filtering: s_filtered =α×s1+(1 -α)×s2; formula (3) e_rpm_filtered =α×e_rpm+(1 -α)×e_rpm_prev; formula (4) p_filtered =α×p+(1 -α)×p_prev; formula (5) Where s1 is the current vehicle speed, s2 is the previous speed, α is the filter coefficient, e_rpm is the current engine speed, e_rpm_prev is the previous engine speed, p is the current throttle position, and p_prev is the previous throttle position. s_filtered is the smoothed current vehicle speed, e_rpm_filtered is the smoothed current engine speed, and p_filtered is the smoothed current throttle position.

[0043] S270: If the current vehicle speed is greater than the vehicle speed threshold, the current engine speed is less than the speed threshold, the current throttle opening is less than or equal to 0, and the current gear is neutral, determine that the vehicle is in a coasting state.

[0044] S280. Count target data of the vehicle in the coasting state; the target data includes at least one of the coasting mileage, the coasting time, and the coasting fuel consumption.

[0045] After collecting the target data of the vehicle in the coasting state, the target data application process is also included, including the following three optional application solutions: The first optional application scenario: analyzing the driver's driving habits based on target data.

[0046] The second optional application scheme: analyzing the vehicle's operating economy based on target data.

[0047] The third optional application scheme: Identify skidding behavior on dangerous road sections based on target data and issue early warnings based on the skidding behavior.

[0048] This embodiment accurately calculates coasting distance, time, and fuel consumption, enabling in-depth analysis of the driver's driving habits and vehicle operating efficiency, providing targeted improvement suggestions to improve driving skills and fuel economy. This embodiment also identifies coasting behavior on hazardous road sections and promptly issues warnings to the driver, mitigating safety hazards caused by improper coasting and improving driving safety.

[0049] When this application is counting the target data of the vehicle in the coasting state, it is necessary to obtain the cumulative mileage and cumulative fuel consumption of the vehicle from the time the T-box is powered on to the current moment. The cumulative mileage and cumulative fuel consumption will be used as basic data to participate in the statistics of the target data in the coasting state. Figure 3 and Figure 4, details the process of obtaining the cumulative mileage and cumulative fuel consumption based on the accumulation period (i.e., the period used to calculate the cumulative mileage and cumulative fuel consumption).

[0050] Figure 3 This is a schematic diagram of a method for calculating accumulated mileage provided in an embodiment of the present application, comprising the following steps: S300: After the T-box is powered on, initialize the current vehicle speed s1 (km / h), the previous vehicle speed s2 (km / h), the current time t1 (s), the previous time t2 (s), and the current accumulated mileage M (km).

[0051] Optionally, the accumulation period may be 0.1s. In this step, s1, s2, t2 and M are all initialized to 0, and the current moment t1 is the current time of the vehicle system.

[0052] Set the default time step of the accumulation period Δt_default to 0.1s. Initialize the anomaly count counter to store the time step Δt of the most recent multiple samplings.

[0053] Subsequently, the wheel speed sensor will collect the vehicle speed and transmit it to the T-box through the CAN network. The update period of s1, s2, t1, t2 and M is 0.1s.

[0054] S310: Is the previous time t2 0? If yes, execute S320; if no, execute S330.

[0055] S320: Determine the time step of the current accumulation period as the default time step, assign the value of t1 to t2, and assign the value of s1 to s2. Return to S310.

[0056] When t2 is 0, the default time step of 0.1s is used to avoid integration failure caused by a time step of 0 and improve the stability of the accumulated mileage calculation.

[0057] S330 : Obtain the time step of the current accumulation period according to the difference between the current time t1 and the previous time t2 .

[0058] To ensure the accuracy of the accumulated mileage calculation, the time step is checked for rationality. If the time step exceeds the normal step range, it is reset to the default value or the historical average time step. For example, the lower bound of the normal step range is Δt_min = 0.08s, and the upper bound of the normal step range is Δt_max = 0.12s. If the time step is less than 0.08s or greater than 0.12s, the time step is reset to 0.1s; alternatively, the time step Δt of the most recent multiple sampling time steps is averaged to obtain the historical average time step Δt_avg, and the time step is set to Δt_avg.

[0059] If the time step is within the normal step range, the time step is corrected according to the historical average time step Δt_avg, see the following formula: Δt_corrected = β×(Δt_raw) + (1 - β)× Δt_avg; formula (6) Where Δt_raw is the time step of the current accumulation period obtained based on the difference between t1 and t2, β is the smoothing weight, Δt_avg is the historical average time step, and Δt_corrected is the corrected time step.

[0060] Optionally, if the time step exceeds the normal step range, the number of exceptions is accumulated by one through the exception count counter; if the number of exceptions exceeds the set threshold (for example, 5 times), it indicates that the time is chaotic, and the previous moment is initialized, for example, the previous moment is initialized to the current moment minus 0.1s.

[0061] S340: Obtain the accumulated mileage of the current accumulation period according to the time step of the current accumulation period, the current vehicle speed, and the vehicle speed at the previous moment, and add up the accumulated mileages of multiple accumulation periods.

[0062] Calculate the cumulative mileage m3 after addition using the following formula: M+ = ((s1 + s2) / 2) × Δt_corrected; Formula (7) Where "+=" is a compound assignment operator that adds the data on the right to the data on the left and assigns the result to the data on the left. Δt_corrected can be obtained according to formula (6) and can be either the default time step or the historical average time step.

[0063] This solution calculates the accumulated mileage in a 100ms cycle and uses the mean integral formula to balance accuracy and computational efficiency, avoiding excessive computing resources and enabling real-time operation in the vehicle controller.

[0064] S350: Assign the value of t1 to t2, and assign the value of s1 to s2. Return to S310.

[0065] The assignment operation is performed so that the calculation can continue in the next accumulation cycle. After each accumulation cycle, the accumulated mileage M will be updated once.

[0066] Figure 4 Schematic diagram of a method for calculating cumulative fuel consumption provided in an embodiment of the present application, comprising the following steps: S400: After the T-box is powered on, the current fuel consumption rate fr1 (L / h), the previous fuel consumption rate fr2 (L / h), the current time t1 (s), the previous time t2 (s), and the current cumulative fuel consumption P (L) are initialized.

[0067] Optionally, the accumulation period may be 0.1s. In this step, fr1, fr2, t2 and P are all initialized to 0, and the current moment t1 is the current time of the vehicle system.

[0068] Set the default time step of the accumulation period Δt_default to 0.1s. Initialize the anomaly count counter to store the time step Δt of the most recent multiple samplings.

[0069] S410: Is the previous time t2 0? If yes, execute S420; if no, execute S430.

[0070] S420: Determine the time step of the current accumulation period as the default time step. Assign the value of t1 to t2, and assign the value of fr1 to fr2. Return to S410.

[0071] When t2 is 0, the default time step of 0.1s is used to avoid the invalidation of integration caused by a time step of 0, thereby improving the stability of the accumulated mileage calculation.

[0072] S430 : Obtain the time step of the current accumulation period according to the difference between the current time t1 and the previous time t2 .

[0073] To ensure the accuracy of the accumulated mileage calculation, the time step is checked for rationality. If the time step exceeds the normal step range, it is reset to the default value or the historical average time step. For example, the lower bound of the normal step range is Δt_min = 0.08s, and the upper bound of the normal step range is Δt_max = 0.12s. If the time step is less than 0.08s or greater than 0.12s, the time step is reset to 0.1s; alternatively, the time step Δt of the most recent multiple sampling time steps is averaged to obtain the historical average time step Δt_avg, and the time step is set to Δt_avg.

[0074] If the time step is within the normal step range, the time step is corrected according to the historical average time step Δt_avg, see formula (6).

[0075] Optionally, if the time step exceeds the normal step range, the number of exceptions is accumulated by one through the exception count counter; if the number of exceptions exceeds the set threshold (for example, 5 times), it indicates that the time is chaotic, and the previous moment is initialized, for example, the previous moment is initialized to the current moment minus 0.1s.

[0076] S440 , obtaining the accumulated fuel consumption of the current accumulation period according to the time step of the current accumulation period, the current fuel consumption rate, and the fuel consumption rate at the previous moment, and adding up the accumulated fuel consumption of multiple accumulation periods.

[0077] Calculate the cumulative fuel consumption P after addition according to the following formula: P+= ((fr1 + fr2) / 2)×Δt_corrected; formula (8) Where "+=" is a compound assignment operator that adds the data on the right to the data on the left and assigns the result to the data on the left. Δt_corrected can be obtained according to formula (6) and can be either the default time step or the historical average time step.

[0078] This solution calculates the cumulative fuel consumption in a 100ms cycle and uses the mean integral formula to balance accuracy and computational efficiency, avoiding excessive computing resources and enabling real-time operation in the vehicle controller.

[0079] S450: Assign the value of t1 to t2, and assign the value of fr1 to fr2. Return to S410.

[0080] The assignment operation is performed so that the calculation can continue in the next accumulation cycle. After each accumulation cycle, the accumulated fuel consumption P will be updated.

[0081] This embodiment uses the average value of the fuel consumption rate at the current moment and the previous moment to calculate the fuel consumption, taking into account both the accuracy of calculation and the occupancy rate of resources.

[0082] Figure 5 This is a flowchart of another method for collecting vehicle coasting data, provided in an embodiment of the present application. This method uses multiple statistical cycles (i.e., cycles used to collect target data) to collect statistics for target data during coasting. Optionally, this method can be deployed in the application layer of an onboard T-box and begin running after the T-box is powered on. Figure 5 The methods shown include: S500: Collect the current state of the vehicle, which includes the current vehicle speed, the current engine speed, the current throttle opening, and the current gear.

[0083] First, before S500, after the T-box is powered on, initialize the current vehicle speed s1, current engine speed e_rpm, current throttle position p, and current gear position d. Initialize the coasting state ss to 0, indicating the initial state. Set the default time step of the statistical period Δt_default to 0.1s. Initialize the abnormality count counter to store the time step Δt of the most recent multiple samplings.

[0084] When S500 is executed, the current vehicle speed s1, the current engine speed e_rpm, the current throttle opening p and the current gear position d are collected through the CAN network.

[0085] S510: Determine a speed threshold value based on a historical average engine speed; and determine a vehicle speed threshold value based on a slope of a road section where the vehicle is located.

[0086] S520: If the current vehicle speed is greater than the vehicle speed threshold, the current engine speed is less than the speed threshold, the current throttle opening is less than or equal to 0, and the current gear is neutral, it is determined that the vehicle is in a coasting state.

[0087] S530: If the vehicle is in a coasting state, obtain the time step of the current statistical period according to the difference between the current moment and the previous moment.

[0088] If the vehicle is in coasting state, set coasting state ss to 1.

[0089] To ensure the accuracy of target data calculations, perform a rationality check on the time step. If the time step exceeds the normal step range, reset it to the default value or the historical average time step. For example, the lower bound of the normal step range is Δt_min = 0.08s, and the upper bound of the normal step range is Δt_max = 0.12s. If the time step is less than 0.08s or greater than 0.12s, reset the time step to 0.1s; alternatively, average the time steps Δt of the most recent multiple samplings to obtain the historical average time step Δt_avg, and set the time step to Δt_avg.

[0090] If the time step is within the normal step range, the time step is corrected according to the historical average time step Δt_avg, see formula (6), which will not be repeated here.

[0091] Optionally, if the time step exceeds the normal step range, the number of exceptions is accumulated by one through the exception count counter; if the number of exceptions exceeds the set threshold (for example, 5 times), it indicates that the time is chaotic, and the previous moment is initialized, for example, the previous moment is initialized to the current moment minus 0.1s.

[0092] S540 , subtract the cumulative fuel consumption f2 from power-on to the previous moment from the cumulative fuel consumption f1 from power-on to the current moment to obtain the fuel consumption of the current statistical period; add the fuel consumption of multiple statistical periods to obtain the coasting fuel consumption of the vehicle in the coasting state.

[0093] S550 , subtract the accumulated mileage m2 from the power-on to the previous moment from the accumulated mileage m1 from the power-on to the current moment to obtain the mileage of the current statistical period; and add the fuel consumption of multiple statistical periods to obtain the coasting mileage of the vehicle in the coasting state.

[0094] Update the coasting status ss to 2, indicating that the vehicle is coasting in neutral. Figure 3 and Figure 4The method shown can obtain the real-time accumulated mileage and real-time accumulated fuel consumption since the vehicle was powered on.

[0095] Indicates entering the neutral gear coasting preparation state. Figure 4 The method shown obtains the cumulative fuel consumption f1 from power-on to the current time and the cumulative fuel consumption f2 from power-on to the previous time. The coasting fuel consumption P1 when the vehicle is coasting is calculated using the following formula.

[0096] P1+= (f1-f2); formula (9) according to Figure 3 The method shown obtains the cumulative mileage m1 from power-on to the current time and the cumulative mileage m2 from power-on to the previous time. The coasting mileage M1 of the vehicle in the coasting state is calculated using the following formula.

[0097] M1+= (m1-m2); Formula (10) S560: Add the time steps of multiple statistical periods to obtain the coasting time of the vehicle in the coasting state.

[0098] Calculate the taxiing time T1 according to the following formula: T1+= Δt_corrected; formula (11) S570: Assign the value of t1 to t2, assign the value of f1 to f2, and assign the value of m1 to m2. Return to S500.

[0099] In this embodiment, the vehicle's real-time coasting mileage, coasting time, and fuel consumption are accumulated through a cycle-by-cycle accumulation process. This data can be stored and accumulated by the vehicle's intelligent terminal or uploaded to a cloud platform for use in applications such as analyzing vehicle driving economy, assessing driver proficiency, and providing warnings for coasting on dangerous roads.

[0100] Based on the above embodiments, this application has the following technical effects: 1. Improve the accuracy of neutral coasting state recognition. Traditional neutral coasting recognition often relies on a single signal (such as throttle, engine speed, etc.) and uses a fixed threshold, which is easily affected by sensor noise, environmental changes, and fluctuations in vehicle operating conditions, resulting in inaccurate judgment. This application introduces a dynamic adaptive threshold adjustment mechanism, which dynamically adjusts the speed threshold and vehicle speed threshold by calculating the historical average engine speed and the slope of the road section on which the vehicle is located in real time, so that the neutral coasting state can be accurately judged under different driving conditions; and the speed threshold and vehicle speed threshold can be automatically adjusted according to the current vehicle operating status and road environment. This not only improves the statistical accuracy under uphill, downhill or other special working conditions, but also provides an adaptation mechanism for different vehicle models, achieving wider applicability.

[0101] 2. Improve the accuracy and robustness of integral data. Previous mileage and fuel consumption calculation algorithms typically use a fixed time step. When data collection intervals are uneven or clock jitter occurs, integral errors accumulate. This application uses an adaptive time step and error correction mechanism to smooth the difference between the current and previous moments (Δt_raw) and the historical average time step (Δt_avg). This automatically compensates for abnormal data when it occurs, ensuring that integral data remains highly accurate and stable over the long term.

[0102] 3. Reduce the impact of data noise on statistical results. Raw signals collected from vehicles (such as vehicle speed, engine speed, and throttle opening) often contain short-term noise and jitter, which can cause fluctuations in neutral coasting state judgment and integral accumulation. This application introduces an adaptive data noise filtering mechanism, using a filtering algorithm to filter the signal, effectively reducing noise interference and ensuring that subsequent processing uses relatively stable signal data.

[0103] 4. Ensure real-time performance and data stability. The entire neutral coasting statistics algorithm is executed cyclically and combined with various adaptive mechanisms (noise filtering, dynamic threshold, and time step adaptive correction). This not only enables real-time monitoring and data statistics, but also has strong self-healing capabilities in the face of data anomalies or emergencies, providing solid data support for real-time evaluation of driving behavior, economic analysis, and safety warnings.

[0104] like Figure 6 As shown, this embodiment provides an electronic device, including: at least one processor; and a memory communicatively connected to at least one processor; wherein, The memory stores instructions executable by at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the above method. The at least one processor in the electronic device is capable of performing the above method, thereby having at least the same advantages as the above method.

[0105] Optionally, the electronic device also includes interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses and can be installed on a common motherboard or installed in other ways as needed. The processor can process instructions executed in the electronic device, including instructions stored in or on the memory to display graphical information of a GUI (Graphical User Interface) on an external input / output device (such as a display device coupled to the interface). In other embodiments, if necessary, multiple processors can be used with multiple memories, and / or multiple buses can be used with multiple memories. Similarly, multiple electronic devices can be connected (for example, as a server array, a group of blade servers, or a multi-processor system), with each device providing part of the necessary operations. Figure 6 A processor 301 is taken as an example.

[0106] Memory 302, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the vehicle coasting data statistical method in the embodiments of the present application. Processor 301 executes the software programs, instructions, and modules stored in memory 302 to execute various functional applications and data processing of the device, thereby implementing the aforementioned vehicle coasting data statistical method.

[0107] The memory 302 may primarily include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function; the data storage area may store data created based on the use of the terminal, etc. Furthermore, the memory 302 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 302 may further include a memory remotely located relative to the processor 301, and these remote memories may be connected to the device via a network. Examples of the aforementioned networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0108] The electronic device may further include: an input device 303 and an output device 304. The processor 301, the memory 302, the input device 303 and the output device 304 may be connected via a bus or other means. Figure 6 The bus connection is taken as an example.

[0109] The input device 303 can receive input digital or character information, and the output device 304 can include a display device, an auxiliary lighting device (e.g., an LED), a tactile feedback device (e.g., a vibration motor), etc. The display device may include, but is not limited to, a liquid crystal display (LCD), a light-emitting diode (LED) display, and a plasma display. In some embodiments, the display device may be a touch screen.

[0110] This embodiment provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to cause a computer to execute the above method. The computer instructions on the computer-readable storage medium are used to cause a computer to execute the above method, thereby having at least the same advantages as the above method.

[0111] The medium in this application may be any combination of one or more computer-readable media. The medium may be a computer-readable signal medium or a computer-readable storage medium. The medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination thereof. More specific examples of media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device.

[0112] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0113] The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wire, optical cable, RF (Radio Frequency), etc., or any suitable combination of the foregoing.

[0114] Computer program code for performing the operations of the present application can be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a stand-alone 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 can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0115] In the above embodiments, all or part of the embodiments can be implemented using software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired connection, such as a coaxial cable, optical fiber, digital subscriber line (DSL), or wireless connection, such as infrared, wireless, or microwave. The computer-readable storage medium can be any available medium that can be accessed by a computer, or a data storage device, such as a server or data center, that includes one or more available media. The available medium can be a magnetic medium (e.g., a floppy disk, hard disk, or magnetic tape), an optical medium, or a semiconductor medium. It is worth noting that the computer-readable storage medium mentioned in the embodiments of the present application may be a non-volatile storage medium, in other words, a non-transitory storage medium.

[0116] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this application can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this application can be achieved. This is not a limitation herein.

[0117] The above specific embodiments do not constitute a limitation on the scope of protection of this application. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application shall be included within the scope of protection of this application.

Claims

1. A statistical method for vehicle coasting data, characterized in that: include: Collecting the current state of the vehicle, including the current vehicle speed, current engine speed, current throttle opening, and current gear position; determining a speed threshold based on historical average engine speed; determining a vehicle speed threshold according to the slope of the road section where the vehicle is located; If the current vehicle speed is greater than the vehicle speed threshold, the current engine speed is less than the speed threshold, the current throttle opening is less than or equal to 0, and the current gear is neutral, determining that the vehicle is in a coasting state; Counting target data of the vehicle in a coasting state; the target data includes at least one of coasting mileage, coasting time, and coasting fuel consumption.

2. The method for counting vehicle coasting data according to claim 1, characterized in that: The speed threshold is determined based on the historical average engine speed, including: Calculate the difference between the historical average engine speed and the coasting reference speed; A speed threshold is obtained according to the coasting reference speed, the difference and a first set adjustment coefficient.

3. The method for counting vehicle coasting data according to claim 1, characterized in that: Determining a vehicle speed threshold according to the slope of the road section where the vehicle is located includes: The slope of the vehicle's current position is collected in real time, and the slopes of various positions on the road section where the vehicle is located are averaged to obtain an average slope; Normalizing the average slope to obtain a slope coefficient; A vehicle speed threshold is obtained according to the coasting reference vehicle speed, the slope coefficient and the second set adjustment coefficient.

4. The method for collecting vehicle glide data according to any one of claims 1 to 3, characterized in that: If the current vehicle speed is greater than the vehicle speed threshold, the current engine speed is less than the speed threshold, the current throttle opening is less than or equal to 0, and the current gear is neutral, before determining that the vehicle is in the coasting state, the method further includes: Smoothing the current vehicle speed according to the vehicle speed at the previous moment to obtain the smoothed current vehicle speed; Smoothing the current engine speed according to the engine speed at the previous moment to obtain the smoothed current engine speed; The current throttle opening is smoothed according to the throttle opening at the previous moment to obtain the smoothed current throttle opening.

5. The method for collecting vehicle glide data according to claim 1, characterized in that: Counting target data of the vehicle in a coasting state includes: If the vehicle is in a coasting state, the time step of the current statistical period is obtained according to the difference between the current moment and the previous moment; The fuel consumption of the current statistical period is obtained by subtracting the cumulative fuel consumption from the time of power-on to the current moment from the cumulative fuel consumption from the time of power-on to the previous moment; and the fuel consumption of multiple statistical periods is added together to obtain the coasting fuel consumption of the vehicle in the coasting state; The mileage of the current statistical period is obtained by subtracting the accumulated mileage from the time the vehicle is powered on to the current moment from the accumulated mileage from the time the vehicle is powered on to the previous moment; and the fuel consumption of multiple statistical periods is added together to obtain the coasting mileage of the vehicle in the coasting state; The time steps of multiple statistical cycles are added together to obtain the coasting time of the vehicle in the coasting state.

6. The method for collecting vehicle glide data according to claim 5, characterized in that: If the vehicle is in a coasting state, after obtaining the time step of the statistical period based on the difference between the current moment and the previous moment, the following steps are also included: If the time step exceeds the normal step range, the time step is reset to a default value or a historical average time step; If the time step is within the normal step range, the time step is corrected according to the historical average time step.

7. The method for collecting vehicle glide data according to claim 6, characterized in that: Also includes: If the time step exceeds the normal step range, the number of abnormalities is accumulated by one; If the number of abnormalities exceeds the set threshold, the previous moment is initialized.

8. A computer program product, characterized in that include: The computer program product stores computer instructions, and when the computer instructions are executed by a processor, the steps of the vehicle coasting data statistics method according to any one of claims 1 to 7 are implemented.

9. A vehicle-mounted controller, characterized in that: include: at least one processor, and a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by at least one of the processors, and the instructions are executed by at least one of the processors to enable the at least one processor to execute the vehicle glide data statistical method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The medium stores computer instructions, and the computer instructions are used to enable a computer to execute the vehicle coasting data statistics method according to any one of claims 1 to 7.

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