Hybrid vehicle control method, device, hybrid vehicle and medium

Abstract

The application provides a control method and device of a hybrid vehicle, the hybrid vehicle and a medium. The method is applied to a vehicle, and the method comprises the following steps: collecting vehicle data and environmental data of the hybrid vehicle in a current working condition; determining a best target state of charge corresponding to the current working condition according to the vehicle data and the environmental data; and controlling a power battery of the hybrid vehicle to discharge or charge according to the best target state of charge. The method can determine the best target state of charge meeting the current working condition based on the data of the current working condition, and the data of different working conditions and working conditions are considered, so that the power battery can discharge or charge according to the best target state of charge to meet the use requirement of the power battery under the current working condition, dynamic and comprehensive control of the best target state of charge is realized, the available space of the battery is better utilized, the cruising range is increased, and the driving performance and the vehicle experience are improved.

Description

Technical Field

[0001] This application relates to the field of vehicles, and more specifically, to a control method, apparatus, hybrid vehicle, and medium for a hybrid electric vehicle. Background Technology

[0002] Traditional energy sources such as oil and natural gas are non-renewable resources and do not align with the concept of sustainable development. Therefore, countries worldwide are increasingly emphasizing the development of new energy vehicles, particularly in the automotive industry. Hybrid vehicles, by adding a hybrid system to existing conventional powertrains, achieve the goal of using both gasoline and electric power, reducing fuel consumption and improving drivability. Hybrid vehicles are one of the mainstream directions in the current automotive industry. By adding a hybrid system, they combine traditional fuel power with electric power, better enhancing vehicle performance. The engine can be fueled by petroleum fuel, and the vehicle battery can be charged, both working together to provide power, improving overall vehicle comfort and enhancing the user experience.

[0003] Hybrid electric vehicles retain engine power while adding electric assist, enabling pure electric drive, pure gasoline drive, and a hybrid drive system. They can also switch driving modes according to external conditions. Due to the addition of a battery system, battery charging and discharging is a crucial control logic. Different operating conditions require control of the battery's target state of charge to achieve better mode switching and overall vehicle comfort.

[0004] Currently, the mainstream hybrid electric vehicle (HEV) drive modes mainly include pure electric, series, and direct drive (parallel hybrid). Different power driving modes can be selected based on different conditions, and the modes can be switched as needed. Due to the addition of the battery system, the vehicle control system needs to control the target state of charge (SOC) of the battery to meet the power battery usage requirements under different operating conditions. Current SOC control methods for HEVs cannot adequately meet the power battery usage requirements under various operating conditions, cannot fully utilize the available battery capacity, and are not conducive to improving vehicle range. Summary of the Invention

[0005] This application provides a control method, device, hybrid vehicle, and medium for a hybrid electric vehicle. The method can adjust the optimal target state of charge based on the current operating conditions of the hybrid electric vehicle, as well as vehicle data and environmental data under the current operating conditions. This allows the power battery to discharge or charge according to the optimal target state of charge to meet the usage requirements of the power battery under the current operating conditions. This achieves dynamic and comprehensive control of the optimal target state of charge, better utilizes the available battery space, increases the driving range, and improves driving performance and user experience.

[0006] In a first aspect, a control method, device, hybrid vehicle, and medium for a hybrid electric vehicle are provided. The method includes: collecting vehicle data and environmental data of the hybrid electric vehicle under its current operating condition; determining the optimal target state of charge corresponding to the current operating condition based on the vehicle data and the environmental data; and controlling the discharge or charging of the hybrid electric vehicle's power battery according to the optimal target state of charge.

[0007] The above technical solution allows for the adjustment of the optimal target state of charge based on the current operating conditions of the hybrid vehicle, as well as the vehicle and environmental data under those conditions. By comprehensively considering various operating conditions and the corresponding vehicle and environmental data, the power battery can be discharged or charged according to the optimal target state of charge to meet the usage requirements of the power battery under the current operating conditions. This achieves dynamic and comprehensive control of the optimal target state of charge, better utilizes the available battery space, increases driving range, and improves driving performance and user experience.

[0008] In conjunction with the first aspect, in some possible implementations, determining the optimal target state of charge (SBC) corresponding to the current operating condition based on the vehicle data and the environmental data includes: identifying vehicle speed, battery temperature, accelerator pedal opening, system mode, and driving mode in the vehicle data, and ambient temperature and atmospheric pressure in the environmental data; determining a basic target SBC based on the vehicle speed, ambient temperature, and battery temperature, and determining a correction value for the target SBC based on one or more of the vehicle speed, accelerator pedal opening, atmospheric pressure, system mode, and driving mode; and correcting the basic target SBC based on the correction value to obtain the optimal target SBC corresponding to the current operating condition.

[0009] The above technical solution can determine the correction value of the basic target state of charge based on different working conditions and vehicle and environmental data under different working conditions. The basic target state of charge is corrected based on the correction value to obtain the optimal target state of charge corresponding to the current working condition. By comprehensively considering various conditions, the impracticality of special working conditions is avoided, and the dynamic adjustment of the target state of charge is realized.

[0010] In conjunction with the first aspect and the above implementation methods, in some possible implementation methods, before controlling the discharge or charging of the hybrid vehicle's power battery according to the optimal target state of charge, the method further includes: determining whether the hybrid vehicle meets a preset downward condition for the target state of charge; if the hybrid vehicle meets the preset downward condition, controlling the hybrid vehicle to enter the target state downward mode, and identifying the vehicle speed, battery temperature and ambient temperature in the vehicle data and the ambient temperature in the environmental data; determining a downward value for the target state of charge based on one or more of the vehicle speed, battery temperature and ambient temperature, and correcting the optimal target state of charge based on the downward value.

[0011] The above technical solution allows the hybrid vehicle to enter a downward mode when it meets the preset downward conditions for the target state of charge, continuously lowering the target state of charge, making greater use of the available battery space, and increasing the driving range.

[0012] In combination with the first aspect and the above implementation methods, in some possible implementation methods, the preset downward conditions include the following conditions: the total driving range of the hybrid vehicle is less than the first preset mileage, the system mode is the first preset power mode, the driving mode is the first preset driving mode, and the actual state of charge of the power battery is greater than the first preset state of charge.

[0013] The above technical solution allows hybrid vehicles to enter a downward mode when preset downward conditions are met, so that subsequent adjustments can be made to achieve the optimal target state of charge.

[0014] In combination with the first aspect and the above implementation methods, in some possible implementation methods, after controlling the hybrid vehicle to enter the target charge state probing mode, the method further includes: determining whether the hybrid vehicle meets the preset probing exit condition; if the hybrid vehicle meets the preset probing exit condition, then controlling the hybrid vehicle to exit the target charge state probing mode and ending the correction of the optimal target charge state.

[0015] The above technical solution allows the hybrid electric vehicle to exit the downward mode when it meets the preset downward exit conditions of the target state of charge.

[0016] In combination with the first aspect and the above implementation methods, in some possible implementation methods, the preset downward exit condition includes any one of the following conditions: the system mode is the second preset power mode, the driving mode is the second preset driving mode, the actual state of charge of the power battery is less than the second preset state of charge, the battery temperature of the power battery is less than the preset temperature, the vehicle travels a second preset mileage in the power reserve mode, and the vehicle speed is greater than the preset vehicle speed and maintained for a preset duration.

[0017] The above technical solution allows a hybrid vehicle to exit the downward mode once any of the preset downward exit conditions are met.

[0018] In combination with the first aspect and the above implementation methods, in some possible implementation methods, before controlling the discharge or charging of the power battery according to the optimal target state of charge, the method further includes: detecting whether the current power mode of the hybrid vehicle is a power reserve mode; if the current power mode is detected to be the power reserve mode, obtaining the user-set value of the target state of charge; and correcting the optimal target state of charge based on the set value.

[0019] The above technical solution enables the optimal target state of charge to be adjusted based on the user-set target state of charge when the hybrid vehicle is in the power reserve mode, thereby meeting user needs.

[0020] Secondly, a control device for a hybrid electric vehicle is provided, comprising: a data acquisition module for acquiring vehicle data and environmental data of the hybrid electric vehicle under the current operating condition; a determination module for determining the optimal target state of charge corresponding to the current operating condition based on the vehicle data and the environmental data; and a control module for controlling the discharge or charging of the hybrid electric vehicle's power battery according to the optimal target state of charge.

[0021] In conjunction with the second aspect, in some possible implementations, the determining module is further configured to: identify vehicle speed, battery temperature, accelerator pedal opening, system mode, and driving mode in the vehicle data, and ambient temperature and atmospheric pressure in the environmental data; determine a basic target state of charge based on the vehicle speed, the ambient temperature, and the battery temperature, and determine a correction value for the target state of charge based on one or more of the vehicle speed, the accelerator pedal opening, the atmospheric pressure, the system mode, and the driving mode; and correct the basic target state of charge based on the correction value to obtain the optimal target state of charge corresponding to the current operating condition.

[0022] In conjunction with the second aspect and the above implementation methods, in some possible implementation methods, the control device of the hybrid electric vehicle further includes: a first judgment module, configured to determine whether the hybrid electric vehicle meets a preset downward condition for the target state of charge before controlling the power battery of the hybrid electric vehicle to discharge or charge according to the optimal target state of charge; if the hybrid electric vehicle meets the preset downward condition, then control the hybrid electric vehicle to enter the target state downward mode, and identify the vehicle speed, battery temperature and ambient temperature in the vehicle data and the ambient temperature in the environmental data; determine the downward value of the target state of charge based on one or more of the vehicle speed, battery temperature and ambient temperature, and correct the optimal target state of charge based on the downward value.

[0023] In combination with the second aspect and the above implementation methods, in some possible implementation methods, the preset downward conditions include the following conditions: the total driving range of the hybrid vehicle is less than the first preset mileage, the system mode is the first preset power mode, the driving mode is the first preset driving mode, and the actual state of charge of the power battery is greater than the first preset state of charge.

[0024] In conjunction with the second aspect and the above implementation methods, in some possible implementation methods, the control device of the hybrid vehicle further includes: a second judgment module, used to determine whether the hybrid vehicle meets a preset downward probe exit condition after controlling the hybrid vehicle to enter the target charge state probe mode; if the hybrid vehicle meets the preset downward probe exit condition, then control the hybrid vehicle to exit the target charge state probe mode and end the correction of the optimal target charge state.

[0025] In combination with the second aspect and the above implementation methods, in some possible implementation methods, the preset downward exit condition includes any one of the following conditions: the system mode is the second preset power mode, the driving mode is the second preset driving mode, the actual state of charge of the power battery is less than the second preset state of charge, the battery temperature of the power battery is less than the preset temperature, the vehicle travels a second preset mileage in the power reserve mode, and the vehicle speed is greater than the preset vehicle speed and maintained for a preset duration.

[0026] In conjunction with the second aspect and the above implementation methods, in some possible implementation methods, the control device of the hybrid vehicle further includes: a detection module, used to detect whether the current power mode of the hybrid vehicle is a power reserve mode before controlling the power battery to discharge or charge according to the optimal target state of charge; if the current power mode is detected to be the power reserve mode, then the user-set value of the target state of charge is obtained; and the optimal target state of charge is corrected based on the set value.

[0027] Thirdly, a hybrid electric vehicle is provided, the hybrid electric vehicle comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the method as described in the first aspect or any possible implementation thereof.

[0028] Fourthly, a computer-readable storage medium is provided that stores computer program code, which, when executed on a computer, causes the computer to perform the methods described in the first aspect or any possible implementation thereof. Attached Figure Description

[0029] Figure 1 This is a flowchart of a control method for a hybrid electric vehicle provided according to an embodiment of this application;

[0030] Figure 2 This is a control logic diagram of the downward probe mode provided according to an embodiment of this application;

[0031] Figure 3 This is a logic diagram for dynamic control of the target state of charge according to an embodiment of this application;

[0032] Figure 4 This is a schematic diagram of the structure of a control device for a hybrid electric vehicle provided according to an embodiment of this application. Detailed Implementation

[0033] The technical solutions in this application will be clearly and thoroughly described below with reference to the accompanying drawings. In the description of the embodiments of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B. "And / or" in the text is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Furthermore, in the description of the embodiments of this application, "multiple" refers to two or more than two.

[0034] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature.

[0035] Before describing the control method of the hybrid electric vehicle in this application, it should be noted that the current mainstream hybrid electric vehicle driving modes mainly include pure electric, series and direct drive. Different power driving can be carried out according to different selection conditions, and the mode can be switched in time.

[0036] With the addition of the battery system, the vehicle control system needs to control the target state of charge (SOC) of the battery. Previous hybrid models could not better adjust the target SOC according to various usage scenarios, considering fewer factors. When the vehicle was in the power reserve mode, there was only a single target SOC value, which could not achieve dynamic adjustment. At the same time, when the vehicle was in pure electric mode for a long time, the target SOC was the same as in hybrid mode, which could not make better use of the available battery space and was not conducive to improving the pure electric range of the vehicle. Therefore, it is necessary to dynamically control the optimal target SOC of hybrid vehicles and control the discharge or charging of the hybrid vehicle's power battery according to the optimal target SOC.

[0037] Figure 1 This is a schematic flowchart of a control method for a hybrid electric vehicle provided in an embodiment of this application.

[0038] For example, such as Figure 1 As shown, the method includes the following steps:

[0039] In step S101, vehicle data and environmental data of the hybrid vehicle under the current operating conditions are collected.

[0040] The current operating condition refers to the operating condition of the hybrid vehicle under the current operating and environmental conditions; vehicle data includes vehicle speed, battery temperature, accelerator pedal opening, system mode (including pure electric mode, pure gasoline mode, hybrid mode, and battery reserve mode, etc.) and driving mode (including sport mode, economy mode, and standard mode, etc.); environmental data includes ambient temperature and atmospheric pressure, etc.

[0041] In step S102, the optimal target state of charge corresponding to the current operating condition is determined based on vehicle data and environmental data.

[0042] It is understood that the embodiments of this application can determine the optimal target state of charge corresponding to the current operating condition based on vehicle data and ambient temperature under the current operating condition of the hybrid vehicle. By comprehensively considering various operating conditions and conditions, different optimal target state of charge is determined under different operating conditions, avoiding the impracticality of special operating conditions, making greater use of the available battery space, increasing the driving range, and thus dynamically adjusting the target state of charge according to the operating condition to give full play to the availability of the battery.

[0043] In this embodiment of the application, determining the optimal target state of charge corresponding to the current operating condition based on vehicle data and environmental data includes: identifying vehicle speed, battery temperature, accelerator pedal opening, system mode, and driving mode in the vehicle data, and ambient temperature and atmospheric pressure in the environmental data; determining a basic target state of charge based on vehicle speed, ambient temperature, and battery temperature, and determining a correction value for the target state of charge based on one or more of vehicle speed, accelerator pedal opening, atmospheric pressure, system mode, and driving mode; and correcting the basic target state of charge based on the correction value to obtain the optimal target state of charge corresponding to the current operating condition.

[0044] It is understood that the embodiments of this application can determine the basic target state of charge based on vehicle speed, ambient temperature and battery temperature, and further determine the correction value of the target state of charge based on one or more of vehicle speed, accelerator pedal opening, atmospheric pressure, system mode and driving mode. The basic target state of charge is corrected according to the correction value to obtain the optimal target state of charge corresponding to the current operating condition. By taking multiple conditions into account, the optimal target state of charge of the hybrid vehicle can be dynamically adjusted according to the operating condition, vehicle data and environmental data, thereby realizing intelligent adjustment.

[0045] The target state of charge acquisition method in this application embodiment may include:

[0046] (1) Set the target state of charge calibration table A based on vehicle speed and battery temperature, and set the target state of charge calibration table B based on vehicle speed and ambient temperature. Take the larger value of the two as the base table for setting the target state of charge, maintain a high target state of charge, and meet the requirements of target state of charge under different environments. That is, the base target state of charge can be determined according to the base table.

[0047] In this embodiment, the target SOC is set based on vehicle speed, battery temperature, and ambient temperature. The target value is increased when the battery or ambient temperature is low to prevent battery depletion. Considering vehicle speed aims to reduce the target SOC at low speeds, minimizing engine shutdown. For example, in low-temperature conditions, if a hybrid vehicle is left idle overnight, the ambient and battery temperatures are not significantly different. However, after the driver drives for a period, the battery temperature rises. While the target SOC won't change much when looking up the table based on ambient temperature, a significant increase in battery temperature will result in a substantial drop in the target SOC. If the hybrid vehicle is then left idle overnight, the battery temperature will decrease, but the target SOC will still be low, potentially unsuitable for low-temperature use. Therefore, the higher of these two factors is chosen to maintain a higher target SOC. This avoids an excessively low battery SOC caused by a large temperature difference between the battery and ambient temperatures, which would compromise usability.

[0048] (2) Set the target state of charge calibration table C based on vehicle speed and accelerator pedal opening, determine the correction value of the target state of charge based on vehicle speed and accelerator pedal opening, and correct the basic target state of charge based on the correction value. High vehicle speed and large accelerator pedal opening improve the target state of charge, which can better correct the target state of charge based on vehicle speed and accelerator pedal opening, provide more power to the hybrid vehicle, and ensure power performance.

[0049] (3) Set the target state of charge calibration table D based on atmospheric pressure, determine the correction value of the basic target state of charge based on atmospheric pressure, and correct the basic target state of charge based on the correction value. The weaker the atmospheric pressure, the less the engine power will be and the weaker the output power. Therefore, improve the target state of charge to provide more power. Take into full account the influence of atmospheric pressure on the target state of charge and improve the driving experience.

[0050] (4) Set the target state of charge calibration table E based on the system mode and driving mode, determine the correction value of the basic target state of charge based on the system mode and driving mode, and correct the basic target state of charge based on the correction value. The target state of charge is different in different modes. Therefore, the different target state of charge required by the hybrid vehicle in different modes is taken into account, so as to meet the power demand in different modes and improve the driving experience.

[0051] The correction value can be confirmed through calibration experiments; no specific limitations are made here.

[0052] It should be noted that in actual use, the embodiments of this application can flexibly combine (2)-(4) to determine the correction value according to the actual working conditions, and correct the basic target state of charge in (1) based on the correction value to obtain the optimal target state of charge. The following will be illustrated by specific examples:

[0053] 1. When the vehicle is in a low-altitude area and is traveling at high speed with a large accelerator pedal opening, vehicle speed and accelerator pedal opening are the main influencing factors affecting the target state of charge. Therefore, the embodiment of this application can obtain the optimal target state of charge by using (1) and (2) above, as follows:

[0054] Since the hybrid vehicle has a high power demand when the vehicle speed is high and the accelerator pedal opening is large, the engine of the hybrid vehicle can work with the most economical fuel consumption and the best power in most cases. Not only can it drive the vehicle smoothly, but it will also generate more energy to generate electricity. Therefore, under such circumstances, the target state of charge can be improved. That is, the correction value is determined according to the vehicle speed and the accelerator pedal opening, and the basic target state of charge in (1) is corrected to obtain the optimal target state of charge, thereby ensuring the power performance of the hybrid vehicle.

[0055] 2. When the vehicle is in a high-altitude area and is traveling at low speed with a small accelerator pedal opening, atmospheric pressure is the main influencing factor affecting the target state of charge. Therefore, the embodiment of this application can obtain the optimal target state of charge by using (1) and (3) above, as follows:

[0056] The embodiments of this application can obtain the optimal target state of charge in high-altitude areas using (1) and (3) as described above, as follows:

[0057] Because the engine intake pressure will be lower in high-altitude areas with thin air, the overall performance of the engine will be affected, the engine capacity will be reduced, and the output power will be weak. Therefore, in the plateau environment, that is, in places with weak atmospheric pressure, the target state of charge can be increased to retain more electricity to enhance power output, thereby improving the driving experience. That is, the correction value of the basic target state of charge is determined according to the atmospheric pressure, and the basic target state of charge in (1) is corrected based on the correction value to obtain the optimal target state of charge.

[0058] 3. When the vehicle is in a high-altitude area and is traveling at high speed and with a large accelerator pedal opening, vehicle speed, accelerator pedal opening, and atmospheric pressure are the main influencing factors affecting the target state of charge. Therefore, this embodiment of the application uses (1), (2), and (3) above to obtain the optimal target state of charge, as follows:

[0059] Based on the basic target state of charge obtained in (1), the target state of charge can be improved in high-altitude areas to retain more power to enhance power output. The correction value of the basic target state of charge is determined according to the atmospheric pressure. When the vehicle speed is high and the accelerator pedal opening is large, the hybrid vehicle has a large power demand and can improve the target state of charge. The correction value of the basic target state of charge is determined according to the vehicle speed and the accelerator pedal opening. The final correction value is calculated according to the weight of atmospheric pressure, vehicle speed and accelerator pedal to the target state of charge and the correction values ​​of both. The optimal target state of charge is obtained by correcting the basic target state of charge using the final correction value.

[0060] 4. In the embodiments of this application, when the hybrid vehicle is in a special mode, such as when the hybrid vehicle is in a snow, mud, or sand power mode, the optimal target state of charge can be obtained by using (1) and (4) above, as follows:

[0061] Due to the different power requirements in different modes, the power requirements of vehicles in special modes such as snow, mud and sand are large (desert, mud extrication). The higher the target state of charge, the more power can be provided. Therefore, the correction value of the basic target state of charge can be determined based on the system mode and driving mode. Based on the correction value, the basic target state of charge in (1) is corrected to obtain the optimal target state of charge.

[0062] 5. The embodiments of this application can also consider (1), (2), (3), and (4) simultaneously to obtain the optimal target state of charge. The vehicle speed, battery temperature, ambient temperature, atmospheric pressure, accelerator pedal opening, system mode, and driving mode are taken into account to achieve dynamic adjustment of the optimal target state of charge of the hybrid vehicle based on the operating conditions, vehicle data, and environmental data, thereby realizing intelligent adjustment.

[0063] In step S103, the power battery of the hybrid vehicle is controlled to discharge or charge according to the optimal target state of charge.

[0064] It is understood that the embodiments of this application can control the discharge or charging of the power battery of the hybrid vehicle according to the optimal target state of charge, so as to realize comprehensive intelligent control of the power battery of the hybrid vehicle and improve driving performance and user experience.

[0065] In this embodiment of the application, before controlling the discharge or charging of the power battery of the hybrid electric vehicle according to the optimal target state of charge, the method further includes: determining whether the hybrid electric vehicle meets the preset downward conditions of the target state of charge; if the hybrid electric vehicle meets the preset downward conditions, controlling the hybrid electric vehicle to enter the target state downward mode, and identifying the vehicle speed, battery temperature and ambient temperature in the vehicle data and the ambient temperature in the environmental data; determining the downward value of the target state of charge based on one or more of the vehicle speed, battery temperature and ambient temperature, and correcting the optimal target state of charge based on the downward value.

[0066] It is understood that, in the embodiments of this application, when the hybrid vehicle meets the preset downward conditions, the hybrid vehicle can be controlled to enter the target state of charge downward mode, and the downward value of the target state of charge can be determined based on one or more of the vehicle speed, battery temperature and ambient temperature of the current operating conditions of the hybrid vehicle. Based on the downward value, the optimal target state of charge is corrected, and the optimal target state of charge is continuously pushed downward, so as to make greater use of the available battery space and increase the driving range of the hybrid vehicle.

[0067] The preset conditions for the downward adjustment include the following: the total driving range of the hybrid vehicle is less than the first preset mileage, the system mode is the first preset power mode, the driving mode is the first preset driving mode, and the actual state of charge of the power battery is greater than the first preset state of charge.

[0068] The first preset mileage can be set according to the specific conditions of the hybrid vehicle, such as 150,000 km; the first preset power mode can be pure electric mode; the first preset driving mode can be standard mode; and the first preset state of charge can be 94%.

[0069] For example, the following will combine Figure 2 Explain the logic behind activating the preset downward probe mode, such as... Figure 2 As shown, the activation of the downward probe mode is related to multiple conditions.

[0070] The activation conditions are as follows: the total mileage of the vehicle is less than 150,000 km; the hybrid system mode of the vehicle is pure electric priority (the default mode of the vehicle); the driving mode of the vehicle is standard (the default mode of the vehicle); and the actual state of charge of the vehicle battery is greater than 94%. The function will be activated when all four conditions are met.

[0071] In this embodiment of the application, after controlling the hybrid vehicle to enter the target charge state probe mode, the method further includes: determining whether the hybrid vehicle meets the preset probe exit condition; if the hybrid vehicle meets the preset probe exit condition, controlling the hybrid vehicle to exit the target charge state probe mode and ending the correction of the optimal target charge state.

[0072] It is understood that, in the embodiments of this application, when the hybrid vehicle meets the preset downward exit conditions, the hybrid vehicle is controlled to exit the target charge state forward mode and the correction of the optimal target charge state is terminated.

[0073] The preset exit conditions include any one of the following: the system mode is the second preset power mode, the driving mode is the second preset driving mode, the actual state of charge of the power battery is less than the second preset state of charge, the battery temperature of the power battery is less than the preset temperature, the vehicle travels a second preset mileage in the power reserve mode, and the vehicle speed is greater than the preset vehicle speed and maintained for a preset duration.

[0074] Among them, the preset temperature, the second preset mileage, the preset vehicle speed and the preset duration can be set according to specific circumstances; the second preset driving mode is a driving mode other than the first driving mode, such as pure oil mode, hybrid mode, battery reserve mode, etc.; the second preset state of charge can be the state of charge at low temperature.

[0075] For example, the exit conditions for the downshifting mode are related to several conditions, including: the vehicle's hybrid system mode is no longer pure electric priority; the vehicle's driving mode is no longer standard; the exit conditions are met based on the battery's state of charge and temperature (based on the exit principle of the downshifting function at low temperature target state of charge); the vehicle travels 80km after switching from CD / CS mode to CS mode; the vehicle speed is greater than 90kph for more than 600s (the vehicle speed is less than 90kph for 30s before recovery). The function exits when any one of the above 5 conditions is met.

[0076] It should be noted that, based on battery protection principles and overall vehicle drivability considerations, a minimum state of charge (SOC) is set for the vehicle's battery to prevent issues such as battery lock-up due to complete depletion and poor drivability in low-charge hybrid mode. If the system detects that a hybrid vehicle user has been driving in pure electric mode after a full charge, the target SOC is adjusted to maximize battery capacity and increase the pure electric range.

[0077] In this embodiment of the application, before controlling the discharge or charging of the power battery according to the optimal target state of charge, the method further includes: detecting whether the current power mode of the hybrid vehicle is a power reserve mode; if the current power mode is detected to be a power reserve mode, obtaining the target state of charge setting value set by the user; and correcting the optimal target state of charge based on the setting value.

[0078] It is understood that, in the embodiments of this application, when the hybrid vehicle is currently in the power mode of the battery reserve mode, the user can set the target state of charge value himself, and the optimal target state of charge is corrected based on the set value to meet the user's vehicle needs.

[0079] Furthermore, the power reserve mode can be divided into two types: forced power reserve mode and intelligent power reserve mode. The influencing factors are the user-set instrument target charge state and vehicle speed. The optimal target charge state is output by taking the larger value between the target charge state and the basic target charge state.

[0080] In addition, in this embodiment of the application, the user can also set a target state of charge (i.e., the maximum target state of charge value) based on the battery characteristics to avoid the battery being fully charged and reducing its lifespan.

[0081] In summary, this application considers multiple operating conditions when setting the target state of charge (SBC) to avoid impracticality in special operating conditions. It also adds a power reserve mode for manually adjusting the SBC setting and a function to probe the SBC setting during pure electric driving to increase the pure electric range. Specifically, it considers conditions such as vehicle speed, ambient temperature, battery temperature, driving mode, and atmospheric pressure. In the power reserve mode, the SBC setting is dynamically adjusted via instrument selection. It also identifies the driver's usage needs. When the hybrid vehicle is continuously driving in pure electric mode, the SBC setting is probed to utilize the available battery space more extensively, increasing the pure electric range and achieving dynamic control of the target SBC of the hybrid vehicle, thus improving the hybrid vehicle user experience.

[0082] The following will combine Figure 3 The target state of charge dynamic control logic of this application is described in detail below:

[0083] (1) Based on the vehicle speed, ambient temperature and battery temperature, the calibration table is set, and the larger of the two is used as the basis for setting the target state of charge (represented as target SOC in the figure).

[0084] (2) The base table is corrected based on vehicle speed and accelerator pedal opening. High vehicle speed and large accelerator pedal opening improve the target state of charge.

[0085] (3) Correct the base table based on atmospheric pressure. The weaker the atmospheric pressure, the higher the target state of charge.

[0086] (4) The base table is modified based on the system mode and driving mode. The target charge state is different in different modes.

[0087] (5) When the target state of charge detection function is activated, the target state of charge is reduced to different degrees based on vehicle speed, ambient temperature and battery temperature, thereby increasing the pure electric range.

[0088] (6) In the power reserve mode, two modes are set: forced power protection and intelligent power protection. The influencing factors are the instrument's state of charge setting value and the vehicle speed. The target value is output by taking the larger value of the basic target state of charge of the hybrid vehicle.

[0089] (7) Based on the battery characteristics, set the maximum target state of charge value to avoid the battery being fully charged, thereby effectively improving the service life of the power battery.

[0090] The control method for hybrid electric vehicles proposed in this application can adjust the optimal target state of charge based on the current operating conditions of the hybrid electric vehicle and the vehicle and environmental data of the operating conditions. It comprehensively considers multiple operating conditions and the corresponding vehicle and environmental data, so that the power battery can discharge or charge according to the optimal target state of charge to meet the usage requirements of the power battery under the current operating conditions, realize the dynamic and comprehensive control of the optimal target state of charge, better utilize the available battery space, increase the driving range, and improve driving performance and user experience.

[0091] Figure 4 This is a schematic diagram of the structure of a control device for a hybrid electric vehicle provided in an embodiment of this application.

[0092] For example, such as Figure 4 As shown, the device 10 may include: a data acquisition module 100, a determination module 200, and a control module 300.

[0093] Acquisition module 100: Used to collect vehicle data and environmental data of the hybrid vehicle under the current operating conditions;

[0094] Determining module 200: used to determine the optimal target state of charge corresponding to the current operating condition based on vehicle data and environmental data;

[0095] Control module 300: Used to control the discharge or charging of the power battery of a hybrid electric vehicle according to the optimal target state of charge.

[0096] In this embodiment, the determining module 200 is further configured to: identify vehicle speed, battery temperature, accelerator pedal opening, system mode, and driving mode in vehicle data, and ambient temperature and atmospheric pressure in environmental data; determine a basic target state of charge based on vehicle speed, ambient temperature, and battery temperature, and determine a correction value for the target state of charge based on one or more of vehicle speed, accelerator pedal opening, atmospheric pressure, system mode, and driving mode; and correct the basic target state of charge based on the correction value to obtain the optimal target state of charge corresponding to the current operating condition.

[0097] In this embodiment of the application, the device 10 further includes a first determination module.

[0098] The first judgment module is used to determine whether the hybrid vehicle meets the preset downward conditions of the target state of charge before controlling the power battery of the hybrid vehicle to discharge or charge according to the optimal target state of charge. If the hybrid vehicle meets the preset downward conditions, the module controls the hybrid vehicle to enter the target state downward mode and identifies the vehicle speed, battery temperature and ambient temperature in the vehicle data and the ambient temperature in the environmental data. The module determines the downward value of the target state of charge based on one or more of the vehicle speed, battery temperature and ambient temperature, and corrects the optimal target state of charge based on the downward value.

[0099] In this application embodiment, the preset down-limit conditions include the following conditions: the total driving range of the hybrid vehicle is less than a first preset mileage, the system mode is a first preset power mode, the driving mode is a first preset driving mode, and the actual state of charge of the power battery is greater than a first preset state of charge.

[0100] In this embodiment of the application, the device 10 further includes a second determination module.

[0101] The second judgment module is used to determine whether the hybrid vehicle meets the preset exit conditions after it enters the target charge state probe mode. If the hybrid vehicle meets the preset exit conditions, the module controls the hybrid vehicle to exit the target charge state probe mode and ends the correction of the optimal target charge state.

[0102] In this application embodiment, the preset exit conditions include any one of the following conditions: the system mode is the second preset power mode, the driving mode is the second preset driving mode, the actual state of charge of the power battery is less than the second preset state of charge, the battery temperature of the power battery is less than the preset temperature, the vehicle travels a second preset mileage in the power reserve mode, and the vehicle speed is greater than the preset vehicle speed and maintained for a preset duration.

[0103] In this embodiment of the application, the device 10 further includes a detection module.

[0104] The detection module is used to detect whether the current power mode of the hybrid vehicle is a power reserve mode before controlling the power battery to discharge or charge according to the optimal target state of charge; if the current power mode is detected to be a power reserve mode, the module obtains the user-set value of the target state of charge; and corrects the optimal target state of charge based on the set value.

[0105] The control device for hybrid electric vehicles proposed in the embodiments of this application can adjust the optimal target state of charge based on the current operating conditions of the hybrid electric vehicle and the vehicle data and environmental data of the current operating conditions. It comprehensively considers multiple operating conditions and the corresponding vehicle data and environmental data, so that the power battery can discharge or charge according to the optimal target state of charge to meet the usage requirements of the power battery under the current operating conditions, realize the dynamic and comprehensive control of the optimal target state of charge, better utilize the available battery space, increase the driving range, and improve driving performance and user experience.

[0106] Furthermore, this application also protects a hybrid electric vehicle, which may include a memory and a processor, wherein the memory stores executable program code, and the processor is used to call and execute the executable program code to perform a control method for a hybrid electric vehicle provided in this application.

[0107] This application also provides a computer-readable storage medium storing computer program code. When the computer program code is run on a computer, the computer executes the aforementioned method steps to implement the control method for a hybrid electric vehicle provided in the above embodiments.

[0108] The apparatus, computer-readable storage medium, or chip provided in the embodiments of this application are all used to execute the corresponding methods provided above. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

[0109] Through the above description of the embodiments, those skilled in the art will understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0110] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0111] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A control method for a hybrid electric vehicle, characterized in that, Includes the following steps: Collect vehicle data and environmental data of hybrid vehicles under the current operating conditions; The optimal target state of charge corresponding to the current operating condition is determined based on the vehicle data and the environmental data. The step of determining the optimal target state of charge (SBC) corresponding to the current operating condition based on the vehicle data and the environmental data includes: identifying vehicle speed, battery temperature, accelerator pedal opening, system mode, and driving mode in the vehicle data, and ambient temperature and atmospheric pressure in the environmental data; determining a basic target SBC based on the vehicle speed, ambient temperature, and battery temperature, and determining a correction value for the target SBC based on one or more of the vehicle speed, accelerator pedal opening, atmospheric pressure, system mode, and driving mode; and correcting the basic target SBC based on the correction value to obtain the optimal target SBC corresponding to the current operating condition. The process further includes: controlling the discharge or charging of the hybrid vehicle's power battery according to the optimal target state of charge; before controlling the discharge or charging of the hybrid vehicle's power battery according to the optimal target state of charge, the process also includes: determining whether the hybrid vehicle meets a preset downward condition for the target state of charge; if the hybrid vehicle meets the preset downward condition, controlling the hybrid vehicle to enter the target state downward mode, and identifying the vehicle speed, battery temperature and ambient temperature in the vehicle data and the ambient temperature in the environmental data; determining a downward value for the target state of charge based on one or more of the vehicle speed, battery temperature and ambient temperature, and correcting the optimal target state of charge based on the downward value.

2. The control method for a hybrid electric vehicle according to claim 1, characterized in that, The preset downward conditions include the following: the total driving range of the hybrid vehicle is less than the first preset mileage, the system mode is the first preset power mode, the driving mode is the first preset driving mode, and the actual state of charge of the power battery is greater than the first preset state of charge.

3. The control method for a hybrid electric vehicle according to claim 1, characterized in that, After controlling the hybrid vehicle to enter the target charge state probe mode, the method further includes: Determine whether the hybrid vehicle meets the preset downward exit conditions; If the hybrid vehicle meets the preset downward exit condition, then the hybrid vehicle is controlled to exit the target charge state forward mode and the correction of the optimal target charge state is terminated.

4. The control method for a hybrid electric vehicle according to claim 3, characterized in that, The preset exit conditions include any one of the following: the system mode is the second preset power mode, the driving mode is the second preset driving mode, the actual state of charge of the power battery is less than the second preset state of charge, the battery temperature of the power battery is less than the preset temperature, the vehicle travels a second preset mileage in the power reserve mode, and the vehicle speed is greater than the preset vehicle speed and maintained for a preset duration.

5. The control method for a hybrid electric vehicle according to claim 1, characterized in that, Before controlling the discharge or charge of the power battery according to the optimal target state of charge, the method further includes: Detect whether the current power mode of the hybrid vehicle is the battery reserve mode; If the current power mode is detected to be the power reserve mode, the target state of charge set by the user is obtained. The optimal target state of charge is corrected based on the set value.

6. A control device for a hybrid electric vehicle, characterized in that, include: The data acquisition module is used to collect vehicle data and environmental data of the hybrid vehicle under the current operating conditions. The determination module is used to determine the optimal target state of charge corresponding to the current operating condition based on the vehicle data and the environmental data; The step of determining the optimal target state of charge (SBC) corresponding to the current operating condition based on the vehicle data and the environmental data includes: identifying vehicle speed, battery temperature, accelerator pedal opening, system mode, and driving mode in the vehicle data, and ambient temperature and atmospheric pressure in the environmental data; determining a basic target SBC based on the vehicle speed, ambient temperature, and battery temperature, and determining a correction value for the target SBC based on one or more of the vehicle speed, accelerator pedal opening, atmospheric pressure, system mode, and driving mode; and correcting the basic target SBC based on the correction value to obtain the optimal target SBC corresponding to the current operating condition. A control module is used to control the discharge or charging of the power battery of a hybrid electric vehicle according to the optimal target state of charge. Before controlling the discharge or charging of the power battery of the hybrid electric vehicle according to the optimal target state of charge, the module further includes: determining whether the hybrid electric vehicle meets a preset downward condition for the target state of charge; if the hybrid electric vehicle meets the preset downward condition, controlling the hybrid electric vehicle to enter the target state downward mode, and identifying the vehicle speed, battery temperature and ambient temperature in the vehicle data and ambient temperature in the environmental data; determining the downward value of the target state of charge based on one or more of the vehicle speed, battery temperature and ambient temperature, and correcting the optimal target state of charge based on the downward value.

7. A hybrid electric vehicle, characterized in that, The hybrid electric vehicle includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the control method of the hybrid electric vehicle as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed, implements the control method for a hybrid electric vehicle as described in any one of claims 1 to 5.

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