Power battery SOC estimation method and system

Abstract

The invention provides a power battery SOC estimation method and system, and the method comprises the steps: selecting SOC estimation methods based on the operation state of a power battery, and determining a target SOC estimation method; estimating the SOC value of the battery according to a target SOC estimation method, and correcting an estimation result based on a target correction coefficient to obtain a real-time SOC value; on the basis of the real-time SOC value, an external power supply critical point of the vehicle is determined by combining actual travel data of the vehicle, when the external power supply critical point is reached, an end early warning is generated, external power supply is interrupted, the real-time SOC value of the power battery of the new energy vehicle is calculated through an open-circuit voltage-ampere-hour integral method estimation method, and the real-time SOC value of the power battery of the new energy vehicle is calculated according to the real-time SOC value. The external power supply critical point of the power battery is determined by combining the actual travel data corresponding to the travel when the driver and the conductor go out, and when the external power supply critical point is reached, early warning is conducted in time to interrupt external power supply, so that it is ensured that the vehicle can return safely with enough electric power.

Description

Technical Field

[0001] The present invention relates to the technical field of battery SOC estimation, and particularly relates to a method and system for estimating the SOC of a power battery. Background Art

[0002] With the increasing scarcity of oil resources, people's demand for new energy is increasing day by day. As a major new energy vehicle, electric vehicles are deeply loved by people and have become one of the main choices for people to travel. With the development of electronic technology, more and more portable electronic devices have emerged, and people's demand for external power supply when going out has also increased. The main power source of an electric vehicle, its internal battery, can be used as a mobile power source to supply power externally. Therefore, many external devices that can be used for electric vehicles have emerged. However, if an electric vehicle supplies power to the outside too much (for example, supplying power to an outdoor lighting lamp for a long time) and cannot replenish the power in time, it is easy to cause the problem that the vehicle cannot complete the journey home. Summary of the Invention

[0003] The present invention provides a method and system for estimating the SOC of a power battery. The real-time SOC value of the power battery of a new energy vehicle is calculated by an open-circuit voltage-Ah integration method, and based on the real-time SOC value, combined with the actual travel data corresponding to the travel distance of the driver and passengers when going out, the external power supply critical point of the power battery is determined, and when the external power supply critical point is reached, a warning is given in time to interrupt the external power supply to ensure that the vehicle has enough power to return safely.

[0004] The present invention provides a method for estimating the SOC of a power battery, including:

[0005] Step 1: Based on the operating state of the power battery, select an SOC estimation method to determine the target SOC estimation method;

[0006] Step 2: Estimate the battery SOC value according to the target SOC estimation method, and correct the estimation result based on the target correction coefficient to obtain the real-time SOC value;

[0007] Step 3: Based on the real-time SOC value, combined with the actual travel data of the vehicle, determine the external power supply critical point of the vehicle, and when the external power supply critical point is reached, generate an end warning and interrupt the external power supply.

[0008] Preferably, in a method for estimating the SOC of a power battery, Step 1 includes:

[0009] When the power battery is in a static state, use the open-circuit voltage method as the target SOC estimation method;

[0010] When the power battery is in an open-circuit state, use the Ah integration method as the target SOC estimation method.

[0011] Preferably, in a method for estimating the state of charge (SOC) of a power battery, step 2 includes:

[0012] Input the current ambient temperature and the charge-discharge rate, and based on the target SOC estimation algorithm, determine the required parameters corresponding to the target correction factor;

[0013] Calculate the required parameters according to the preset ambient temperature correction factor algorithm or the charge-discharge rate correction factor algorithm to obtain the target correction factor;

[0014] Obtain the initial SOC value, and estimate the battery SOC value based on the target SOC estimation algorithm and the initial SOC value to obtain the estimated SOC value;

[0015] Based on the target correction factor, correct the estimated SOC value to obtain the real-time SOC value.

[0016] Preferably, in a method for estimating the state of charge (SOC) of a power battery, step 3 includes:

[0017] Obtain the actual travel data of the vehicle, and based on the actual travel data, determine the round-trip route of the vehicle and its road conditions;

[0018] Compare the road conditions corresponding to the round-trip route to obtain the driving difference. Based on the actual power consumption during the vehicle's incoming journey and combined with the driving difference, determine the preliminary predicted power consumption corresponding to the return journey route;

[0019] Based on the cloud database corresponding to the vehicle and the trip type corresponding to the current trip, obtain multiple similar travel data, mark the sunrise and sunset times and arrival times for the multiple similar travel data, and extract features corresponding to the return time based on the marking results to obtain the return time feature;

[0020] Based on the return time feature, combine the sunrise and sunset times corresponding to the current date and the arrival time during the incoming journey for prediction to obtain the predicted return time of the current trip;

[0021] Predict the road conditions during the return journey according to the predicted return time of the current trip to obtain the estimated return time, compare the estimated return time with the actual time taken during the incoming journey to obtain the driving time difference;

[0022] Based on the driving time difference and the average power consumption during congestion, obtain the power consumption difference between the round-trip routes, and correct the preliminary predicted power consumption according to the power consumption difference between the round-trip routes to obtain the estimated power consumption for the return journey;

[0023] Based on the real-time SOC value, determine the actual remaining power of the vehicle at present, and according to the actual remaining power and the estimated power consumption for the return journey, determine the external power supply critical point of the vehicle;

[0024] When there are multiple return routes for the vehicle, predict the power consumption for the return trips of multiple return routes simultaneously, obtain the predicted power consumption for multiple return trips, and use the maximum predicted power consumption for the return trip as the final predicted power consumption for the return trip.

[0025] Preferably, in a method for estimating the state of charge (SOC) of a power battery, step 3 further includes:

[0026] Determine the current available power of the vehicle based on the external power supply critical point.

[0027] Obtain the total output power of all current external power supplies corresponding to the vehicle, and based on the output power and the current available power, obtain the external power supply time.

[0028] When the external power supply time is less than or equal to the preset value, send a notice of refusal of external energy supply to the driver and passengers, and interrupt the power transmission of the external device connection port.

[0029] Otherwise, allow the external device connection port to supply power externally, and send a reminder of the expected power supply time to the driver and passengers.

[0030] Preferably, in a method for estimating the state of charge (SOC) of a power battery, when allowing the external device connection port to supply power externally, it includes:

[0031] Compare the real-time SOC value with the critical value corresponding to the external power supply critical point in real time. When it is detected that the current real-time SOC value is equal to the critical value, immediately interrupt the power transmission of the external device connection port, and generate an end warning for voice broadcast.

[0032] Preferably, in a method for estimating the state of charge (SOC) of a power battery, compare the road conditions of the round-trip routes to obtain the driving differences. Based on the actual power consumption during the vehicle's incoming journey and combining the driving differences, determine the preliminary predicted power consumption corresponding to the return route, including:

[0033] Obtain the return route that is the same as the incoming route as the first target route, and use the remaining return routes as the second target routes.

[0034] Based on the actual driving data during the incoming journey, determine the actual road conditions corresponding to each section, and flip the actual road conditions to obtain the return journey road conditions.

[0035] Compare the actual road conditions with the return journey road conditions to determine the power-saving sections and power-consuming sections for the return journey, as well as the power-consuming sections and power-saving sections for the incoming journey.

[0036] And compare the power-consuming sections for the return journey with the power-consuming sections for the incoming journey to obtain the length of the power-consuming difference, and at the same time compare the power-saving sections for the return journey with the power-saving sections for the incoming journey to obtain the length of the power-saving difference.

[0037] Based on the preset average power consumption and power-consuming difference length for uphill driving of the vehicle, as well as the preset average power consumption and power-saving difference length for downhill driving, calculate the predicted power consumption difference between the coming route and the first target route;

[0038] Obtain the actual power consumption of the vehicle when coming. Based on the actual power consumption of the vehicle when coming and the predicted power consumption difference, obtain the preliminary predicted power consumption of the first target route;

[0039] Respectively obtain the maximum speed limit values of each section of the first target route and the second target route;

[0040] Based on the preset average power consumption of the vehicle in each speed range, combined with the maximum speed limit value corresponding to each section, calculate the predicted power consumption corresponding to each section respectively;

[0041] According to the predicted power consumption of all sections corresponding to the first target route, calculate the first speed predicted power consumption of the first target route. Compare the first speed predicted power consumption with the preliminary predicted power consumption to obtain the prediction error rate;

[0042] Respectively obtain the predicted power consumption of all sections corresponding to different second target routes, and calculate the second speed predicted power consumption corresponding to different second target routes;

[0043] Based on the prediction error rate, correct the second speed predicted power consumption to obtain the preliminary predicted power consumption corresponding to the second target route.

[0044] Preferably, in a method for estimating the state of charge (SOC) of a power battery, based on the marked result corresponding to the return time, extract features of the return time, including:

[0045] Based on the sunrise and sunset times corresponding to the return dates of multiple similar travel data, generate multiple travel time axes, and mark different arrival times and return times on the corresponding travel time axes;

[0046] And calculate the time difference between each arrival time and the return time. Based on the time difference, extract the outdoor travel duration feature of the driver and passengers;

[0047] Simultaneously, based on the sunrise and sunset times, determine the solar altitude corresponding to different return times. Based on the solar altitude, extract the outdoor travel return node feature of the driver and passengers;

[0048] According to the outdoor travel duration feature and the outdoor travel return node feature, generate the return time feature.

[0049] The present invention provides a system for estimating the state of charge (SOC) of a power battery, including:

[0050] An estimation method determination module, which is used to select an SOC estimation method based on the operating state of the power battery and determine the target SOC estimation algorithm;

[0051] An SOC value real-time calculation module, which is used to estimate the battery SOC value according to the target SOC estimation algorithm and correct the estimation result based on the target correction coefficient to obtain the real-time SOC value;

[0052] An external power supply warning module, which is used to determine the external power supply critical point of the vehicle based on the real-time SOC value and the actual travel data of the vehicle, and generate an end warning and interrupt the external power supply when the external power supply critical point is reached.

[0053] Compared with the prior art, the present invention has the following beneficial effects: Based on the operating state of the power battery, the present invention selects an SOC estimation method, determines the target SOC estimation algorithm, and realizes the combination of multiple power battery SOC estimation methods, which is beneficial to improving the accuracy of the power battery SOC value estimation; then estimates the battery SOC value according to the target SOC estimation algorithm and corrects the estimation result based on the target correction coefficient to obtain the real-time SOC value, effectively improving the estimation accuracy of the real-time SOC value and providing a reliable basis for the accurate determination of the external power supply critical point; finally, based on the real-time SOC value and the actual travel data of the vehicle, determine the external power supply critical point of the vehicle, and generate an end warning and interrupt the external power supply when the external power supply critical point is reached, which can effectively prevent the situation that an electric vehicle (for example: camping) supplies power to external devices excessively during outdoor travel, resulting in the vehicle being unable to return safely. The present invention calculates the real-time SOC value of the power battery of a new energy vehicle through the open-circuit voltage-Ah integration method to improve the accuracy of SOC value monitoring, and determines the external power supply critical point of the power battery based on the real-time SOC value and the actual travel data corresponding to the coming and going distances of the driver and passengers during the outing, and when the external power supply critical point is reached, issues a warning in time to interrupt the external power supply to ensure that the vehicle has enough power to return safely.

[0054] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained by the structures specifically pointed out in this application document.

[0055] The technical solutions of the present invention will be further described in detail below with reference to the drawings and embodiments. Description of the Drawings

[0056] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention, and do not constitute a limitation to the present invention. In the drawings:

[0057] Figure 1 It is a flowchart of a method for estimating the state of charge (SOC) of a power battery according to the present invention;

[0058] Figure 2 It is a flowchart of step 2 of a method for estimating the state of charge (SOC) of a power battery according to the present invention;

[0059] Figure 3 It is a structural diagram of a system for estimating the state of charge (SOC) of a power battery according to the present invention. Specific embodiments

[0060] 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 only for the purpose of illustrating and explaining the present invention, and are not intended to limit the present invention.

[0061] Embodiment 1:

[0062] The present invention provides a method for estimating the state of charge (SOC) of a power battery, as Figure 1 shown, including:

[0063] Step 1: Based on the operating state of the power battery, select a method for estimating the SOC and determine the target SOC estimation method;

[0064] Step 2: Estimate the SOC value of the battery according to the target SOC estimation method and correct the estimation result based on the target correction coefficient to obtain the real-time SOC value;

[0065] Step 3: Based on the real-time SOC value, combine the actual travel data of the vehicle to determine the external power supply critical point of the vehicle, and generate an end warning and interrupt the external power supply when the external power supply critical point is reached.

[0066] In this embodiment, the SOC estimation method includes two methods: the open-circuit voltage method and the ampere-hour integration method.

[0067] Advantages of the above technical solution: Based on the operating state of the power battery, the present invention selects the SOC estimation method, determines the target SOC estimation algorithm, and realizes the combination of multiple power battery SOC estimation methods, which is beneficial to improving the accuracy of the power battery SOC value estimation; then estimates the battery SOC value according to the target SOC estimation algorithm, and corrects the estimation result based on the target correction coefficient to obtain the real-time SOC value, effectively improving the estimation accuracy of the real-time SOC value and providing a reliable basis for accurately determining the external power supply critical point; finally, based on the real-time SOC value and combined with the actual travel data of the vehicle, the external power supply critical point of the vehicle is determined, and when the external power supply critical point is reached, an end warning is generated and the external power supply is interrupted, which can effectively prevent the situation that an electric vehicle going outdoors (for example: camping) over-supplies power to external devices and causes the vehicle to be unable to return safely. The present invention calculates the real-time SOC value of the power battery of a new energy vehicle through the open circuit voltage-Ah integration method estimation method to improve the accuracy of SOC value monitoring, and based on the real-time SOC value, combined with the actual travel data corresponding to the incoming journey of the driver and passengers going out, determines the external power supply critical point of the power battery, and when the external power supply critical point is reached, gives a warning in time to interrupt the external power supply to ensure that the vehicle has enough power to return safely.

[0068] Embodiment 2:

[0069] Based on Embodiment 1, step 1 includes:

[0070] When the power battery is in a static state, the open circuit voltage method estimation method is used as the target SOC estimation algorithm;

[0071] When the power battery is in an open circuit state, the Ah integration method estimation method is used as the target SOC estimation algorithm.

[0072] Advantages of the above technical solution: When the power battery is in a static state, the open circuit voltage method is used to estimate the SOC value of the power battery; when the power battery is in a charging and discharging state, the SOC value estimated by the open circuit voltage method in the previous static state of the power battery is used as the initial SOC 0 , and then the charging and discharging amount during the time to the previous static state is calculated by using the Ah integration method, and finally the real-time SOC value is obtained. Through the estimation method combining the open circuit voltage method and the Ah integration method, when the power battery is static, the open circuit voltage method can be used to re-estimate the battery SOC value, correct the error that appears in the Ah integration method in the previous working period, and effectively improve the estimation accuracy of the power battery SOC estimation system.

[0073] Embodiment 3:

[0074] Based on Embodiment 1, step 2 includes:

[0075] Step 201: Input the current ambient temperature and the charge-discharge rate, and determine the required parameters corresponding to the target correction factor based on the target SOC estimation method;

[0076] Step 202: Calculate the required parameters according to the preset ambient temperature correction factor algorithm or the charge-discharge rate correction factor algorithm to obtain the target correction factor;

[0077] Step 203: Obtain the initial SOC value, and estimate the battery SOC value according to the target SOC estimation method and the initial SOC value to obtain the estimated SOC value;

[0078] Step 204: Correct the estimated SOC value based on the target correction factor to obtain the real-time SOC value.

[0079] In this embodiment, the required parameters include the current ambient temperature and the charge-discharge rate. When the open-circuit voltage method is used to estimate the SOC value, the required parameter is the current ambient temperature; when the ampere-hour integration method is used to estimate the SOC value, the required parameters are the current ambient temperature and the charge-discharge rate.

[0080] In this embodiment, the ambient temperature correction factor algorithm is:

[0081] K T = 6.683×10 -8 T 4 + 2.753×10 -7 T 3 - 4.394×10 -4 T 2 + 2.01×10 -2 T + 0.75

[0082] Among them, K T is the ambient temperature correction factor, and T is the ambient temperature.

[0083] In this embodiment, the charge-discharge rate correction factor algorithm is:

[0084] K I = -2.133×10 -5 I 4 - 1.353×10 -2 I 3 + 1.033×10 -2 I 2 - 6.870×10 -3 I + 1.003

[0085] Among them, K I is the charge-discharge rate correction factor, and I is the battery discharge current.

[0086] Beneficial effects of the above technical solution: According to the ambient temperature, the present invention obtains the corresponding ambient temperature correction coefficient to correct the SOC value estimated by the open circuit voltage method to obtain the initial SOC value estimated by the ampere-hour integration method, realizing the compensation for the influence of too high or too low ambient temperature on the open circuit voltage. Then, according to the ambient temperature and the charge-discharge rate, the corresponding correction coefficient is obtained to correct the SOC estimated by the ampere-hour integration method again to obtain the real-time SOC value, realizing the compensation for the influence of temperature and charge-discharge rate on the battery capacity, effectively improving the estimation accuracy of the SOC value of the power battery, providing a relatively high-precision remaining power of the electric vehicle for the driver and passengers, facilitating the driver and passengers to plan the itinerary, and at the same time, being conducive to improving the accuracy of determining the external power supply critical point in the future.

[0087] Embodiment 4:

[0088] Based on Embodiment 1, Step 3 includes:

[0089] Obtain the actual travel data of the vehicle. Based on the actual travel data, determine the round-trip route of the vehicle and its road condition environment;

[0090] Compare the road condition environments corresponding to the round-trip routes to obtain the driving differences. Based on the actual power consumption during the vehicle's coming journey and in combination with the driving differences, determine the preliminary predicted power consumption corresponding to the return journey route;

[0091] Based on the cloud database corresponding to the vehicle and the travel type corresponding to the current journey, obtain multiple similar travel data. Mark the sunrise and sunset times and arrival times for the multiple similar travel data. Based on the marking results, extract features for the return time to obtain the return time features;

[0092] Based on the return time features, combine the sunrise and sunset times corresponding to the current date and the arrival time during the coming journey for prediction to obtain the predicted return time of the current journey;

[0093] Predict the road conditions during the return journey according to the predicted return time of the current journey to obtain the expected return time. Compare the expected return time with the actual time taken during the coming journey to obtain the driving time difference;

[0094] Based on the driving time difference and the average power consumption during congestion, obtain the power consumption difference between the round-trip routes. Correct the preliminary predicted power consumption according to the power consumption difference between the round-trip routes to obtain the expected power consumption during the return journey;

[0095] Based on the real-time SOC value, determine the actual power storage of the vehicle at present. According to the actual power storage and the expected power consumption during the return journey, determine the external power supply critical point of the vehicle;

[0096] Wherein, when there are multiple return routes for the vehicle, the return power consumption of the multiple return routes is predicted synchronously to obtain multiple predicted return power consumptions, and the maximum predicted return power consumption is used as the final predicted return power consumption.

[0097] In this embodiment, the actual travel data refers to the road conditions and vehicle operation data when the vehicle comes (including but not limited to power consumption and speed of each section).

[0098] In this embodiment, the round-trip route includes the actual route when coming and the predicted return route for the return journey by navigation. Among them, there may be one or multiple return routes.

[0099] In this embodiment, the driving difference refers to the difference between the power-saving sections and power-consuming sections in the round-trip route.

[0100] In this embodiment, the road conditions refer to the road surface conditions, for example, uphill, downhill, flat, etc.

[0101] In this embodiment, the preliminary predicted power consumption refers to the prediction of the return power consumption without considering the driving road conditions on the return route.

[0102] In this embodiment, the same type of travel data refers to the driving data of the same travel category as the current one (for example: short-distance play, camping and other outdoor sports travels).

[0103] In this embodiment, the arrival time when coming refers to the time of arriving at the outdoor operation destination.

[0104] In this embodiment, the sunrise and sunset times corresponding to the current date are obtained by the vehicle-associated weather forecast.

[0105] In this embodiment, the average power consumption in congestion refers to the average power consumption calculated based on the power consumption data during the waiting time of the vehicle in the congested section.

[0106] In this embodiment, the driving road conditions on the return journey refer to the driving conditions on each return route during the return journey.

[0107] In this embodiment, the driving time difference refers to the time difference between the actual driving time of the route when coming and the predicted driving time corresponding to the predicted return route by navigation.

[0108] The power consumption difference of the round-trip route refers to the product of the driving time difference and the average power consumption in congestion.

[0109] Beneficial effects of the above technical solution: First, the present invention obtains the actual travel data of the vehicle, and based on the actual travel data, determines the round-trip route of the vehicle and its road conditions; compares the road conditions corresponding to the round-trip route to obtain the driving differences, and based on the actual power consumption during the vehicle's incoming journey, combines the driving differences to determine the preliminary predicted power consumption corresponding to the return route, realizing the preliminary prediction of the power consumption during the return journey. Then, based on the cloud database corresponding to the vehicle and the travel type corresponding to the current journey, multiple similar travel data are obtained, the sunrise and sunset times and arrival times are marked for the multiple similar travel data, and feature extraction is performed on the return time corresponding to the marking results to obtain the return time features; based on the return time features, combined with the sunrise and sunset times corresponding to the current date and the arrival time during the incoming journey, the predicted return time of the current journey is obtained; according to the predicted return time of the current journey, the road conditions during the return journey are predicted to obtain the estimated time for the return journey, and the estimated time for the return journey is compared with the actual time taken during the incoming journey to obtain the driving time difference; based on the driving time difference and the average power consumption during congestion, the power consumption difference between the round-trip routes is obtained, and the preliminary predicted power consumption is corrected according to the power consumption difference between the round-trip routes to obtain the estimated power consumption for the return journey. Integrating the actual driving road conditions with the environmental road conditions is beneficial to improving the accuracy of the power consumption during the journey home, ensuring that the predicted power consumption for the return journey can fully meet the needs of the passengers and driver to arrive home safely. Finally, based on the real-time SOC value, the current actual battery capacity of the vehicle is determined, and according to the actual battery capacity and the estimated power consumption for the return journey, the external power supply critical point of the vehicle is determined, providing a basis for the timely warning of external power supply. When there are multiple return routes for the vehicle, the power consumption for the return journey is predicted for multiple return routes simultaneously to obtain multiple estimated power consumptions for the return journey, and the maximum estimated power consumption for the return journey is used as the final estimated power consumption for the return journey, which can fully ensure that the vehicle's power supply to external devices will not affect the passengers and driver's homecoming plan.

[0110] Embodiment 5:

[0111] Based on the embodiment 4, step 3 further includes:

[0112] Based on the external power supply critical point, determine the current available power of the vehicle;

[0113] Obtain the total output power of all current external power supplies corresponding to the vehicle, and based on the output power and the current available power, obtain the external power supply time;

[0114] When the external power supply time is less than or equal to the preset value, send a notice of refusal of external energy supply to the passengers and driver, and interrupt the power transmission of the external device connection port;

[0115] Otherwise, allow the external device connection port to supply power externally, and send a reminder of the estimated power supply time to the passengers and driver.

[0116] Beneficial effects of the above technical solution: The present invention determines the current available power of the vehicle through the external power supply critical point; obtains the total output power of all current external power supplies corresponding to the vehicle, and estimates the external power supply time based on the output power and the current available power. When the external power supply time is less than or equal to a preset value, a notification of refusal of external energy supply is sent to the driver and passengers, and the power transmission of the external device connection port is interrupted, avoiding unnecessary device connections in the case of too little available power and a very short power supply time. When the external device connection port is allowed to supply power externally, a reminder of the estimated power supply time is sent to the driver and passengers, facilitating the driver and passengers to adjust the outdoor operation plan in advance.

[0117] Embodiment 6:

[0118] Based on Embodiment 5, when the external device connection port is allowed to supply power externally, it includes:

[0119] Compare the real-time SOC value with the critical value corresponding to the external power supply critical point in real time. When it is detected that the current real-time SOC value is equal to the critical value, immediately interrupt the power transmission of the external device connection port and generate an end warning for voice broadcast.

[0120] Beneficial effects of the above technical solution: The present invention compares the real-time SOC value with the critical value corresponding to the external power supply critical point in real time. When it is detected that the current real-time SOC value is equal to the critical value, immediately interrupt the power transmission of the external device connection port and generate an end warning for voice broadcast, avoiding the situation where the driver and passengers do not understand the actual power of the vehicle or the vehicle's power consumption plan is unclear and resulting in an inability to return smoothly, and maximizing the guarantee of sufficient return power for the vehicle in an outdoor environment where charging is inconvenient.

[0121] Embodiment 7:

[0122] Based on Embodiment 4, it is characterized in that the road conditions of the round-trip route are compared to obtain the driving difference. Based on the actual power consumption of the vehicle when coming, combined with the driving difference, the preliminary predicted power consumption corresponding to the return route is determined, including:

[0123] Obtain the return route that is the same as the route when coming as the first target route, and use the remaining return route as the second target route;

[0124] Based on the actual driving data when coming, determine the actual road conditions corresponding to each section, and flip the actual road conditions to obtain the return road conditions;

[0125] Compare the actual road conditions with the return road conditions to determine the power-saving sections and power-consuming sections of the return journey, as well as the power-consuming sections and power-saving sections of the journey when coming;

[0126] Compare the power-consuming sections of the return journey with those of the incoming journey to obtain the power-consuming difference length. At the same time, compare the power-saving sections of the return journey with those of the incoming journey to obtain the power-saving difference length;

[0127] Based on the preset average power consumption for uphill driving of the vehicle, the power-consuming difference length, the preset average power consumption for downhill driving, and the power-saving difference length, calculate the predicted power consumption difference between the incoming route and the first target route;

[0128] Obtain the actual power consumption of the vehicle during the incoming journey. Based on the actual power consumption of the vehicle during the incoming journey and the predicted power consumption difference, obtain the preliminary predicted power consumption of the first target route;

[0129] Obtain the maximum speed limit values for each section of the first target route and the second target route respectively;

[0130] Based on the preset average power consumption of the vehicle within each speed range and in combination with the maximum speed limit value corresponding to each section, calculate the predicted power consumption corresponding to each section respectively;

[0131] According to the predicted power consumption of all sections corresponding to the first target route, calculate the first speed predicted power consumption of the first target route. Compare the first speed predicted power consumption with the preliminary predicted power consumption to obtain the prediction error rate;

[0132] Obtain the predicted power consumption of all sections corresponding to different second target routes respectively, and calculate the second speed predicted power consumption corresponding to different second target routes;

[0133] Based on the prediction error rate, correct the second speed predicted power consumption to obtain the preliminary predicted power consumption corresponding to the second target route.

[0134] In this embodiment, the remaining return route refers to other navigation-predicted return routes except for the return route that is the same as the incoming route.

[0135] In this embodiment, flipping the actual road conditions correspondingly means flipping the road surface conditions of each section on the future route. For example, changing an uphill section to a downhill section and vice versa. If it is a flat road, it remains unchanged.

[0136] In this embodiment, a power-saving section refers to a section on the incoming route or the first target route that can reduce the power output power, such as a downhill section; a power-consuming section refers to a section on the incoming route or the first target route that requires an increase in the power output power, such as an uphill section.

[0137] In this embodiment, the power-consuming difference length refers to the difference between the power-consuming sections of the return journey and those of the incoming journey; the power-saving difference length refers to the difference between the power-saving sections of the return journey and those of the incoming journey.

[0138] In this embodiment, the preset average power consumption for uphill driving and the preset average power consumption for downhill driving refer to the ideal power consumption data that is calculated based on the vehicle test data before the vehicle leaves the factory and is pre-stored in the database.

[0139] In this embodiment, the maximum speed limit value refers to the highest speed corresponding to each road section.

[0140] In this embodiment, the average power consumption within each speed range is calculated based on the vehicle test data before the vehicle leaves the factory. This data is pre-stored in the database.

[0141] In this embodiment, the predicted power consumption of the first speed is obtained by predicting the power consumption of the first target route based on the maximum speed limit values of each road section of the first target route.

[0142] In this embodiment, the power consumption of the second target route is predicted based on the maximum speed limit values of each road section of the second target route to obtain the power consumption of the second target route.

[0143] In this embodiment, the driving difference refers to the difference in road conditions during the driving process between the incoming route and the return route.

[0144] The beneficial effects of the above technical solution: By comparing the road conditions of the incoming route with those of the corresponding return route of the same road, the present invention obtains the difference in road conditions during the driving process. Then, based on the difference in road conditions, combined with the preset average power consumption for uphill driving and the preset average power consumption for downhill driving, the predicted power consumption difference between the incoming route and the corresponding return route of the same road is predicted. Finally, based on the actual power consumption of the vehicle during the incoming journey and the predicted power consumption difference, the preliminary predicted power consumption of the first target route is obtained. Then, the power consumption of the first target route is predicted falsely based on the maximum speed limit values of each road section of the first target route to obtain the predicted power consumption of the first speed. The predicted power consumption of the first speed is compared with the preliminary predicted power consumption to obtain the prediction error rate. Finally, the predicted power consumption of the second speed of the second target route is obtained by truly predicting the power consumption of the second target route based on the maximum speed limit values of each road section of the second target route, and the preliminary predicted power consumption of the remaining return routes is obtained through the prediction error rate for the predicted power consumption of the second speed, effectively improving the prediction accuracy of the power consumption of each return route.

[0145] Example 8:

[0146] Based on the embodiment 3, feature extraction is performed on the return time corresponding to the marking result to obtain the return time feature, including:

[0147] Based on the sunrise and sunset times corresponding to the return dates of multiple similar travel data, multiple travel time axes are generated, and different arrival times and return times are marked on the corresponding travel time axes;

[0148] Calculate the time difference between each arrival time and the return time, and based on the time difference, extract the outdoor travel duration characteristics of the driver and passengers;

[0149] Synchronously, based on the sunrise and sunset times, determine the solar altitude corresponding to different return times, and based on the solar altitude, extract the outdoor travel return node characteristics of the driver and passengers;

[0150] Generate the return time characteristics according to the outdoor travel duration characteristics and the outdoor travel return node characteristics.

[0151] Beneficial effects of the above technical solution: The present invention extracts features corresponding to the return time of the marking result, obtains the return time features for extraction, and correlates the outdoor activity habits of the driver and passengers (from the performance of the outdoor activity duration) with the natural environment conditions, which is beneficial to improving the accuracy of return time prediction.

[0152] Example 9:

[0153] The present invention provides a power battery SOC estimation system, as Figure 3 shown, including:

[0154] An estimation method determination module, configured to select an SOC estimation method based on the operating state of the power battery to determine the target SOC estimation algorithm;

[0155] An SOC value real-time calculation module, configured to estimate the battery SOC value according to the target SOC estimation algorithm and correct the estimation result based on the target correction coefficient to obtain the real-time SOC value;

[0156] An external power supply warning module, configured to determine the external power supply critical point of the vehicle based on the real-time SOC value in combination with the actual travel data of the vehicle, and generate an end warning and interrupt the external power supply when the external power supply critical point is reached.

[0157] Advantages of the above technical solution: The present invention determines the operating state of the module based on the power battery through an estimation method, selects an SOC estimation method, determines the target SOC estimation algorithm, and combines multiple power battery SOC estimation methods, which is beneficial to improving the accuracy of the power battery SOC value estimation. Then, the SOC value real-time calculation module estimates the battery SOC value according to the target SOC estimation algorithm and corrects the estimation result based on the target correction coefficient to obtain the real-time SOC value, effectively improving the estimation accuracy of the real-time SOC value and providing a reliable basis for accurately determining the external power supply critical point. Finally, the external power supply warning module determines the external power supply critical point of the vehicle based on the real-time SOC value and the actual travel data of the vehicle, and generates an end warning and interrupts the external power supply when the external power supply critical point is reached, which can effectively prevent the situation that an electric vehicle (e.g., camping) supplies power to external devices excessively during outdoor travel, resulting in the vehicle being unable to return safely. The present invention calculates the real-time SOC value of the power battery of a new energy vehicle through the open circuit voltage-Ah integration method estimation method to improve the accuracy of SOC value monitoring, and determines the external power supply critical point of the power battery according to the real-time SOC value and the actual travel data corresponding to the incoming journey of the driver and passengers. When the external power supply critical point is reached, a warning is given in a timely manner to interrupt the external power supply to ensure that the vehicle has sufficient power to return safely.

[0158] Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A power battery SOC estimation method, characterized in that: include: Step 1: Based on the operating status of the power battery, select the SOC estimation method and determine the target SOC estimation method; Step 2: Estimate the battery SOC value according to the target SOC estimation method, and correct the estimation result based on the target correction coefficient to obtain the real-time SOC value; Step 3: Based on the real-time SOC value and the actual travel data of the vehicle, the vehicle's external power supply critical point is determined, and when the external power supply critical point is reached, an end warning is generated and the external power supply is interrupted.

2. A power battery SOC estimation method according to claim 1, characterized in that: Step 1 includes: When the power battery is in a stationary state, the open circuit voltage estimation method is used as the target SOC estimation method; When the power battery is in an open circuit state, the ampere-hour integration method is used as the target SOC estimation method.

3. A power battery SOC estimation method according to claim 1, characterized in that: Step 2 includes: Input the current ambient temperature and charge / discharge rate, and determine the required parameters corresponding to the target correction coefficient based on the target SOC estimation method; According to the preset ambient temperature correction coefficient algorithm or the charge and discharge rate correction coefficient algorithm, the demand parameters are calculated to obtain the target correction coefficient; Obtaining an initial SOC value, estimating the battery SOC value according to the target SOC estimation method and the initial SOC value, and obtaining an estimated SOC value; Based on the target correction coefficient, the estimated SOC value is corrected to obtain the real-time SOC value.

4. A power battery SOC estimation method according to claim 1, characterized in that: Step 3 includes: Acquire actual travel data of the vehicle, and determine the round-trip route of the vehicle and its road conditions based on the actual travel data; Compare the road conditions of the return route and the return route to obtain the driving difference. Based on the actual power consumption of the vehicle on the way and the driving difference, determine the initial predicted power consumption of the return route. Based on the cloud database corresponding to the vehicle and the trip type corresponding to the current trip, multiple similar travel data are obtained, sunrise and sunset times and arrival times are marked for the multiple similar travel data, and features are extracted corresponding to the return time based on the marking results to obtain return time features; Based on the return time feature, combined with the sunrise and sunset time corresponding to the current date and the arrival time, the predicted return time of the current trip is obtained; Predicting the return road conditions according to the predicted return time of the current trip to obtain an estimated return time, and comparing the estimated return time with the actual time taken to arrive to obtain a travel time difference; Based on the travel time difference and the average power consumption in congestion, the power consumption difference of the round-trip route is obtained, and the initial predicted power consumption is corrected according to the power consumption difference of the round-trip route to obtain the estimated power consumption for the return trip; Based on the real-time SOC value, the vehicle's current actual power storage capacity is determined, and based on the actual power storage capacity and the estimated power consumption on the return journey, the vehicle's external power supply critical point is determined.

5. A power battery SOC estimation method according to claim 4, characterized in that: When the vehicle has multiple return routes, the return power consumption is predicted for the multiple return routes simultaneously to obtain multiple return estimated power consumptions, and the maximum return estimated power consumption is used as the final return estimated power consumption.

6. A power battery SOC estimation method according to claim 5, characterized in that: Step 3 also includes: Based on the external power supply critical point, determine the current available power of the vehicle; Obtain the total output power of all current external power supplies corresponding to the vehicle, and obtain the external power supply time based on the total output power and the current available power; When the external power supply time is less than or equal to the preset value, an external power supply rejection notification is sent to the driver and passengers, and the power supply to the external device connection port is interrupted; Otherwise, the external device connection port is allowed to supply power to the outside, and a reminder of the estimated power supply time is sent to the driver and passengers.

7. A power battery SOC estimation method according to claim 6, characterized in that: When the external device connection port is allowed to supply power externally, it includes: The real-time SOC value is compared with the critical value corresponding to the external power supply critical point in real time. When it is detected that the current real-time SOC value is equal to the critical value, the power transmission to the external device connection port is immediately interrupted, and an end warning is generated for voice broadcast.

8. A power battery SOC estimation method according to claim 5, characterized in that: Compare the road conditions of the return route to obtain the driving difference. Based on the actual power consumption of the vehicle when it comes and the driving difference, determine the preliminary predicted power consumption corresponding to the return route, including: The same return route as the coming route is obtained as the first target route, and the remaining return route is obtained as the second target route; Based on the actual driving data on the way here, the actual road condition environment corresponding to each road section is determined, and the actual road condition environment is correspondingly flipped to obtain the return road condition environment; Compare the actual road condition environment with the return road condition environment to determine the return route saving circuit section and the return route toll point section as well as the return route toll point section and the return route saving circuit section; The return route is compared with the toll route on the way in, and the difference in the length of the toll route is obtained. At the same time, the return route is compared with the toll route on the way in, and the difference in the length of the toll route is obtained. Based on the vehicle's preset uphill average power consumption and power-cost difference length and the preset downhill average power consumption and power-saving difference length, the predicted power consumption difference between the original route and the first target route is calculated; The actual power consumption of the vehicle when it arrives is obtained, and the preliminary predicted power consumption of the first target route is obtained according to the difference between the actual power consumption of the vehicle when it arrives and the predicted power consumption; Obtain the maximum speed limit value of each section of the first target route and the second target route respectively; Based on the average power consumption of the vehicle in each speed range, combined with the maximum speed limit value corresponding to each road section, the predicted power consumption corresponding to each road section is calculated respectively; Calculate the predicted power consumption of the first speed of the first target route according to the predicted power consumption of all sections corresponding to the first target route, compare the predicted power consumption of the first speed with the preliminary predicted power consumption, and obtain a prediction error rate; Respectively obtain the predicted power consumption of all road sections corresponding to different second target routes, and calculate the predicted power consumption of the second speeds corresponding to different second target routes; The second speed predicted power consumption is corrected based on the prediction error rate to obtain a preliminary predicted power consumption corresponding to the second target route.

9. A power battery SOC estimation method according to claim 3, characterized in that: Based on the marking results, feature extraction is performed on the return time to obtain the return time features, including: Based on the sunrise and sunset times corresponding to the return dates of multiple similar travel data, multiple travel time axes are generated, and different arrival times and return times are marked on the corresponding travel time axes; The time difference between each arrival time and return time is calculated, and based on the time difference, the outdoor travel duration characteristics of the drivers and passengers are extracted; Synchronously, based on the sunrise and sunset times, determine the sun altitude corresponding to different return times, and based on the sun altitude, extract the outdoor travel return node features of drivers and passengers; The return time characteristics are generated based on the outdoor travel duration characteristics and the outdoor travel return node characteristics.

10. A power battery SOC estimation system, characterized in that: include: An estimation method determination module, used to select an SOC estimation method based on the operating state of the power battery and determine a target SOC estimation method; The SOC value real-time calculation module is used to estimate the battery SOC value according to the target SOC estimation method, and correct the estimation result based on the target correction coefficient to obtain the real-time SOC value; The external power supply warning module is used to determine the vehicle's external power supply critical point based on the real-time SOC value and the vehicle's actual travel data, and generate an end warning and interrupt the external power supply when the external power supply critical point is reached.

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