Energy regulation and control method for hybrid vehicle, and vehicle

Abstract

An energy regulation and control method for a hybrid vehicle, comprising: on the basis of real-time driving data and a driving condition standard library corresponding to the hybrid vehicle, determining a current driving condition and a current condition category (S31); on the basis of the current driving condition, the current condition category and road condition information, performing driving condition prediction on the hybrid vehicle to obtain a condition prediction result, the road condition information comprising at least one of the following: real-time road condition data, and predicted road condition data (S32); on the basis of the condition prediction result and a current battery level corresponding to the hybrid vehicle, determining a target energy regulation and control strategy corresponding to a current operation mode of the hybrid vehicle (S33); and, according to the target energy regulation and control strategy, performing real-time regulation and control on an engine output power and a driving motor output power of the hybrid vehicle (S34). The method improves an intelligent level and accuracy of the energy regulation and control method of the hybrid vehicle. Further provided is a vehicle.

Description

Energy control method for hybrid vehicle and vehicle Technical Field

[0001] The present invention relates to the field of hybrid vehicle energy control, and in particular to an energy control method for a hybrid vehicle and a hybrid vehicle. Background Art

[0002] The rational management and distribution of energy in hybrid vehicles is a key technology for achieving energy conservation and emission reduction, and energy control strategies are also a core technology for reducing vehicle fuel consumption. Currently, related technologies usually regulate the energy of the vehicle based on the characteristics of the battery itself. Specifically, for example, the range of available battery power is obtained based on the temperature and internal resistance curve, and then the battery output is controlled within this available power range during vehicle driving to achieve rational energy regulation; for another example, the battery power is managed in sections, and then the power battery output is controlled according to the power output response relationship to achieve rational energy regulation. However, the energy regulation methods provided by related technologies only use the characteristics of the battery itself for energy regulation, resulting in poor regulation accuracy and low intelligence level of the regulation method.

[0003] From the above analysis, it can be seen that there is currently no effective solution to the problems of low intelligence level and low accuracy of the energy control methods for hybrid vehicles provided by the above-mentioned related technologies.

[0004] Summary of the Invention

[0005] The embodiments of the present invention provide an energy control method for a hybrid vehicle and a vehicle, so as to at least solve the technical problems of low intelligence level and low accuracy of the energy control method for a hybrid vehicle provided by the related art.

[0006] According to one aspect of an embodiment of the present invention, there is provided an energy control method for a hybrid vehicle, including:

[0007] Based on real-time driving data and a driving condition standard library corresponding to the hybrid vehicle, a current driving condition and a current condition category are determined; based on the current driving condition, the current condition category, and road condition information, a driving condition prediction is performed on the hybrid vehicle to obtain a condition prediction result, wherein the road condition information includes at least one of the following: real-time road condition data and predicted road condition data; using the condition prediction result and the current battery power corresponding to the hybrid vehicle, a target energy control strategy corresponding to the current operating mode of the hybrid vehicle is determined, wherein the current operating mode is one of the following: a motor-driven operating mode, an engine-driven operating mode, a hybrid-driven operating mode, a brake energy recovery operating mode, a driving charging operating mode, and a rapid acceleration operating mode; and the engine output power and the drive motor output power of the hybrid vehicle are controlled in real time according to the target energy control strategy.

[0008] Optionally, based on the real-time driving data and the driving condition standard library corresponding to the hybrid vehicle, determining the current driving condition and the current operating condition category includes: using the sample operating condition set, historical driving data and target operating condition characteristic parameters corresponding to the hybrid vehicle to construct a driving condition standard library, wherein the driving condition standard library includes multiple candidate driving conditions, and the multiple candidate driving conditions belong to multiple operating condition categories; based on the real-time driving data, determining the current driving condition from the multiple candidate driving conditions, and determining the current operating condition category from the multiple operating condition categories.

[0009] Optionally, constructing a driving condition standard library using a sample operating condition set, historical driving data, and target operating condition characteristic parameters corresponding to a hybrid vehicle includes: extracting features from the sample operating condition set to obtain multiple operating condition characteristic parameters, wherein the sample operating condition set includes: simulation test operating conditions and actual vehicle test operating conditions; using the fuel economy parameters corresponding to the hybrid vehicle as optimization indicators, performing orthogonal optimization analysis on the multiple operating condition characteristic parameters, and selecting target operating condition characteristic parameters from the multiple operating condition characteristic parameters; segmenting the historical driving data of the hybrid vehicle according to a first time length to obtain multiple operating condition segments; and performing cluster analysis on the multiple operating condition segments based on the target operating condition characteristic parameters to generate a driving condition standard library.

[0010] Optionally, based on real-time driving data, determining the current driving condition from multiple candidate driving conditions, and determining the current operating condition category from multiple operating condition categories include: performing feature extraction on the real-time driving data according to the target operating condition characteristic parameters to obtain extraction results; performing fuzzy recognition on the extraction results to obtain recognition results; comparing and matching the recognition results with a driving condition standard library, determining the current driving condition from multiple candidate driving conditions, and determining the current operating condition category from multiple operating condition categories.

[0011] Optionally, using the operating condition prediction result and the current battery power corresponding to the hybrid vehicle to determine the target energy control strategy corresponding to the current operating mode includes: using the operating condition prediction result, the current battery power and the current driving data of the hybrid vehicle to determine the current operating mode, wherein the operating condition prediction result includes at least: predicted operating condition category, predicted operating condition duration, and the current driving data includes at least: accelerator pedal opening, brake pedal opening; according to the current operating mode, selecting the target control strategy from multiple candidate energy control strategies.

[0012] Optionally, real-time control of the engine output power and drive motor output power of a hybrid vehicle according to a target energy control strategy includes: determining an engine torque target value and a drive motor torque target value using the target energy control strategy; determining a first target power based on the engine torque target value, and determining a second target power based on the drive motor torque target value; and controlling the hybrid vehicle to adjust the engine output power to the first target power, and adjust the drive motor output power to the second target power.

[0013] Optionally, when the current operating mode is the driving charging operating mode, the target energy control strategy is the driving charging torque distribution strategy, and determining the target engine torque value and the target drive motor torque value using the target energy control strategy includes: in response to the required torque at the transmission input end of the hybrid vehicle being less than or equal to the torque economy lower limit value, determining the target engine torque value as the torque economy lower limit value according to the driving charging torque distribution strategy, wherein the torque economy lower limit value is determined by a preset lower limit rule of the engine speed and the engine economy parameter; in response to the required torque at the transmission input end being greater than the torque economy lower limit value and less than the torque economy upper limit value, determining the target engine torque value as the torque economy upper limit value according to the driving charging torque distribution strategy, wherein the torque economy upper limit value is determined by a preset upper limit rule of the engine speed and the engine economy parameter; in response to the required torque at the transmission input end being greater than or equal to the torque economy upper limit value, determining the target engine torque value as the required torque at the transmission input end according to the driving charging torque distribution strategy; and determining the target drive motor torque value as the difference between the required torque at the transmission input end and the target engine torque value according to the driving charging torque distribution strategy.

[0014] Optionally, when the current operating mode is the hybrid drive operating mode, the target energy control strategy is a hybrid drive torque distribution strategy, and using the target energy control strategy to determine the engine torque target value and the drive motor torque target value includes: in response to the transmission input end required torque of the hybrid vehicle being less than or equal to a first torque upper limit value, determining the engine torque target value as the transmission input end required torque according to the hybrid drive torque distribution strategy, wherein the first torque upper limit value is determined by first engine characteristic information of the hybrid vehicle in the hybrid drive operating mode; in response to the transmission input end required torque being greater than the first torque upper limit value, determining the engine torque target value as the first torque upper limit value according to the hybrid drive torque distribution strategy; and determining the drive motor torque target value as the difference between the transmission input end required torque and the engine torque target value according to the driving charging torque distribution strategy.

[0015] Optionally, when the current operating mode is the rapid acceleration operating mode, the target energy control strategy is the rapid acceleration torque distribution strategy, and using the target energy control strategy to determine the engine torque target value and the drive motor torque target value includes: in response to the required torque at the transmission input end of the hybrid vehicle being less than or equal to the second torque upper limit value, determining the engine torque target value as the required torque at the transmission input end according to the rapid acceleration torque distribution strategy, wherein the second torque upper limit value is determined by the second engine characteristic information of the hybrid vehicle in the rapid acceleration operating mode; in response to the required torque at the transmission input end being greater than the second torque upper limit value, determining the engine torque target value as the second torque upper limit value according to the rapid acceleration torque distribution strategy; and determining the drive motor torque target value as the difference between the required torque at the transmission input end and the actual value of the engine torque according to the rapid acceleration torque distribution strategy, wherein the actual value of the engine torque is collected in real time by the engine controller.

[0016] According to another aspect of an embodiment of the present invention, a vehicle is provided, comprising an on-board memory and an on-board processor, wherein a computer program is stored in the on-board memory, and the on-board processor is configured to run the computer program to execute any one of the aforementioned energy control methods for a hybrid vehicle.

[0017] In an embodiment of the present invention, a current driving condition and a current operating condition category are first determined based on real-time driving data corresponding to the hybrid vehicle and a driving condition standard library. Next, a driving condition prediction is performed on the hybrid vehicle based on the current driving condition, the current operating condition category, and road condition information to obtain a driving condition prediction result, wherein the road condition information includes at least one of the following: real-time road condition data and predicted road condition data. The driving condition prediction result and the current battery charge corresponding to the hybrid vehicle are then used to determine a target energy control strategy corresponding to a current operating mode of the hybrid vehicle, wherein the current operating mode is one of the following: a motor-driven operating mode, an engine-driven operating mode, a hybrid-driven operating mode, a brake energy recovery operating mode, a driving charging operating mode, and a rapid acceleration operating mode. Finally, the engine output power and the drive motor output power of the hybrid vehicle are controlled in real time according to the target energy control strategy.

[0018] It is easy to understand that the above-mentioned method provided by the present invention achieves the purpose of accurately predicting the driving conditions and intelligently controlling the energy of the hybrid vehicle by first predicting the future driving conditions of the hybrid vehicle and then combining the predicted conditions with the current battery current to determine the target energy control strategy, thereby achieving the technical effect of improving the accuracy of the conditions prediction results and enhancing the intelligence level of the hybrid vehicle energy control, thereby solving the technical problems of low intelligence level and low accuracy of the hybrid vehicle energy control methods provided by related technologies. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are provided to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0020] FIG1 is a hardware structure block diagram of a vehicle terminal optionally configured as an energy control method for a hybrid vehicle according to an embodiment of the present invention;

[0021] FIG2 is a schematic diagram of a hybrid system of a hybrid vehicle according to an embodiment of the present invention;

[0022] FIG3 is a flow chart of an energy control method for a hybrid vehicle according to an embodiment of the present invention;

[0023] FIG4 is a schematic diagram of a process for constructing an optional hybrid vehicle driving condition according to an embodiment of the present invention;

[0024] FIG5 is a schematic diagram of an optional energy control process of a hybrid vehicle according to an embodiment of the present invention;

[0025] FIG6 is a flow chart of an optional energy control process of a hybrid vehicle according to an embodiment of the present invention;

[0026] FIG7 is a schematic diagram of a torque distribution control unit of an optional vehicle controller of a hybrid vehicle according to an embodiment of the present invention;

[0027] FIG8 is a schematic diagram of an optional driving charging torque zone division process according to an embodiment of the present invention;

[0028] FIG9 is a structural block diagram of an energy control device for a hybrid vehicle according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] According to an embodiment of the present invention, a method embodiment of an energy control method for a hybrid vehicle is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0032] FIG1 is a block diagram of the hardware structure of a vehicle terminal configured as an energy control method for a hybrid vehicle according to an embodiment of the present invention. As shown in FIG1 , the vehicle terminal (or a mobile device in communication with the vehicle) may include one or more processors 102 (the processor 102 may include, but is not limited to, a processing device such as a microcontroller unit (MCU) or a programmable logic device (FPGA)), a memory 104 configured to store data, and a transmission device 106 configured to perform communication functions. In addition, the device may also include: a display device 110, input / output devices 108, a universal serial bus (USB) port (which may be included as one of the ports of a computer bus, not shown in the figure), a network interface (not shown in the figure), a power supply (not shown in the figure), and / or a camera (not shown in the figure). It will be understood by those skilled in the art that the structure shown in FIG1 is merely illustrative and does not limit the structure of the vehicle terminal 1 described above. For example, the vehicle terminal may also include more or fewer components than those shown in FIG1 , or have a configuration different from that shown in FIG1 .

[0033] It should be noted that the one or more processors 102 and / or other data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuit may be a single independent processing module, or may be fully or partially integrated into any of the other components in the vehicle terminal (or mobile device).

[0034] Memory 104 can be configured to store software programs and modules for application software, such as the program instructions / data storage device corresponding to the hybrid vehicle energy control method in the embodiments of the present invention. Processor 102 executes the software programs and modules stored in memory 104 to execute various functional applications and data processing, thereby implementing the hybrid vehicle energy control method described above. Memory 104 can include high-speed random access memory (RAM) and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, memory 104 may further include memory remotely located from processor 102, which can be connected to the vehicle terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0035] The transmission device 106 is configured to receive or transmit data via a network. A specific example of such a network may include a wireless network provided by a communications provider of the vehicle terminal. In one embodiment, the transmission device 106 includes a network interface controller (NIC) that can be connected to other network devices via a base station to enable communication with the Internet. In another embodiment, the transmission device 106 may be a radio frequency (RF) module configured to communicate with the Internet wirelessly.

[0036] FIG2 is a schematic diagram of a hybrid system for a hybrid vehicle according to an embodiment of the present invention. As shown in FIG2 , the hybrid system includes at least: an engine management system (EMS) 201 configured to control the operating state and performance of an engine 202, including but not limited to controlling fuel supply, controlling the ignition system, controlling the air intake system, monitoring engine operating state, and adjusting engine performance; the engine 202 configured to drive the hybrid vehicle; a battery management system (BMS) 203 configured to monitor the state of a power battery 205 to prevent abnormal battery conditions such as overcharging, overdischarging, and overheating; and a vehicle control unit (VCU) 204, which is the core control component of the hybrid vehicle and is configured to send control instructions to one or more other components of the hybrid vehicle (e.g., the BMS 203, the motor controller 206, and the EMS 201) to control their operation.

[0037] Still as shown in FIG2 , the hybrid system of a hybrid vehicle further includes at least: a power battery 205 configured to store and release electrical energy and provide power for the vehicle; a motor controller (MCU) 206 configured to control the motor 207 to operate in a set direction, speed, angle, and response time; the motor 207 configured to provide additional power to assist the engine 202 in driving the vehicle, and may also be configured to convert kinetic energy into electrical energy by recovering braking energy and store it in the power battery 205; a clutch 208 configured to cut off or transmit power output by the engine 202; a transmission 209 configured to transmit the speed and torque from the engine 202; and a transmission controller (TCU) 210 configured to control and manage the transmission 209.

[0038] Under the above operating environment, an embodiment of the present invention provides an energy control method for a hybrid vehicle as shown in Figure 3. Figure 3 is a flow chart of an energy control method for a hybrid vehicle according to an embodiment of the present invention. As shown in Figure 3, the embodiment shown in Figure 3 may include at least the following implementation steps, that is, it may be a technical solution implemented by steps S31 to S34.

[0039] Step S31, determining the current driving condition and the current condition category based on the real-time driving data corresponding to the hybrid vehicle and the driving condition standard library;

[0040] Step S32, predicting the driving condition of the hybrid vehicle based on the current driving condition, the current driving condition category, and the road condition information to obtain a driving condition prediction result, wherein the road condition information includes at least one of the following: real-time road condition data and predicted road condition data;

[0041] Step S33, using the operating condition prediction result and the current battery charge of the hybrid vehicle, determining a target energy control strategy corresponding to the current operating mode of the hybrid vehicle, wherein the current operating mode is one of the following: motor drive operating mode, engine drive operating mode, hybrid drive operating mode, brake energy recovery operating mode, driving charging operating mode, and rapid acceleration operating mode;

[0042] In step S34 , the engine output power and the drive motor output power of the hybrid vehicle are controlled in real time according to the target energy control strategy.

[0043] In the optional technical solutions provided in steps S31 to S34 above, the real-time driving data may include, but is not limited to, real-time driving distance, real-time vehicle speed, maximum speed, and real-time acceleration (deceleration). This real-time driving data can be used to characterize the real-time driving conditions of the hybrid vehicle. The standard library of driving conditions may include, but is not limited to, the New European Driving Cycle (NEDC), which can be used to evaluate vehicle fuel economy and emissions and can simulate urban and suburban driving conditions based on driving conditions with different speeds and dwell times; the Worldwide Harmonized Light Vehicles Test Cycle (WLTC), which can be used to evaluate light vehicle fuel consumption and emissions. Compared to the NEDC, the WLTC includes higher average speeds, longer driving distances, and more real-world driving data; and the California Light-Duty Test Cycle (CLTC), which can be used to evaluate light vehicle fuel economy and emissions.

[0044] In the optional technical solutions provided in steps S31 to S34 above, the real-time traffic condition data and predicted traffic condition data may include, but are not limited to, congested conditions, urban conditions, suburban conditions, and highway conditions. It should be noted that congested conditions refer to conditions in the heart of a city with heavy traffic and frequent vehicle starts and stops; urban conditions refer to conditions in areas within the city with smooth traffic and low vehicle speeds; suburban conditions refer to conditions in densely populated areas outside the city with medium or high vehicle speeds; and highway conditions refer to conditions on highways.

[0045] In the optional technical solution provided in steps S31 to S34 above, the current battery charge level can be directly read from the hybrid vehicle's instrument panel. The target energy control strategy can be used to intelligently allocate and manage the vehicle's energy in the hybrid vehicle's current operating mode, thereby meeting the energy requirements of the hybrid vehicle's various systems while reducing excess energy and fuel consumption.

[0046] In an embodiment of the present invention, a current driving condition and a current operating condition category are first determined based on real-time driving data corresponding to the hybrid vehicle and a driving condition standard library. Next, a driving condition prediction is performed on the hybrid vehicle based on the current driving condition, the current operating condition category, and road condition information to obtain a driving condition prediction result, wherein the road condition information includes at least one of the following: real-time road condition data and predicted road condition data. The driving condition prediction result and the current battery charge corresponding to the hybrid vehicle are then used to determine a target energy control strategy corresponding to a current operating mode of the hybrid vehicle, wherein the current operating mode is one of the following: a motor-driven operating mode, an engine-driven operating mode, a hybrid-driven operating mode, a brake energy recovery operating mode, a driving charging operating mode, and a rapid acceleration operating mode. Finally, the engine output power and the drive motor output power of the hybrid vehicle are controlled in real time according to the target energy control strategy.

[0047] It is easy to understand that the above-mentioned method provided by the present invention achieves the purpose of accurately predicting the driving conditions and intelligently controlling the energy of the hybrid vehicle by first predicting the future driving conditions of the hybrid vehicle and then combining the predicted conditions with the current battery current to determine the target energy control strategy, thereby achieving the technical effect of improving the accuracy of the conditions prediction results and enhancing the intelligence level of the hybrid vehicle energy control, thereby solving the technical problems of low intelligence level and low accuracy of the hybrid vehicle energy control methods provided by related technologies.

[0048] The above method of the embodiment of the present invention is further introduced below.

[0049] In an optional embodiment, in step S31, based on the real-time driving data corresponding to the hybrid vehicle and the driving condition standard library, determining the current driving condition and the current driving condition category includes:

[0050] Step S311: constructing a driving condition standard library using a sample driving condition set, historical driving data, and target driving condition characteristic parameters corresponding to the hybrid vehicle, wherein the driving condition standard library includes a plurality of candidate driving conditions, each of which belongs to a plurality of driving condition categories;

[0051] Step S312 : determining a current driving condition from a plurality of candidate driving conditions based on the real-time driving data, and determining a current operating condition category from a plurality of operating condition categories.

[0052] In the optional technical solutions provided in steps S311 and S312 above, the sample operating condition set may include, but is not limited to, sample operating condition data selected from the aforementioned driving condition standard library and sample operating condition data selected from actual vehicle test data. The target operating condition characteristic parameter may be used to evaluate the fuel economy of a hybrid vehicle. Specifically, for example, the target operating condition characteristic parameter is the average speed of the hybrid vehicle. When the average speed of the hybrid vehicle in a first time period is less than the average speed of the hybrid vehicle in a second time period, it can be determined that the fuel economy of the hybrid vehicle in the first time period is better than that in the second time period. The multiple operating condition categories may include, but are not limited to, congested operating conditions, urban operating conditions, suburban operating conditions, and highway operating conditions.

[0053] In an optional embodiment, in step S311, constructing a driving condition standard library using a sample driving condition set, historical driving data, and target driving condition characteristic parameters corresponding to a hybrid vehicle includes:

[0054] Step S3111: extracting features from a sample operating condition set to obtain a plurality of operating condition characteristic parameters, wherein the sample operating condition set includes: simulation test operating conditions and actual vehicle test operating conditions;

[0055] Step S3112: Using the fuel economy parameter corresponding to the hybrid vehicle as an optimization index, performing orthogonal optimization analysis on multiple operating condition characteristic parameters, and selecting a target operating condition characteristic parameter from the multiple operating condition characteristic parameters;

[0056] Step S3113, dividing the historical driving data of the hybrid vehicle into segments according to the first time length to obtain a plurality of operating condition segments;

[0057] Step S3114: performing cluster analysis on multiple operating condition segments based on the target operating condition characteristic parameters to generate a driving condition standard library.

[0058] In the optional technical solutions provided in steps S3111 to S3114 above, the multiple operating condition characteristic parameters may include, but are not limited to, driving distance, average vehicle speed, average driving speed, maximum vehicle speed, maximum acceleration, maximum deceleration, average acceleration, average deceleration, idling time, number of stops, and percentage of idling time. The simulated test operating conditions may be operating condition data obtained from a simulation test of a hybrid vehicle using simulation software. It should be noted that the simulation software may include, but is not limited to, CarSim, ADAS, CRUISE, Simulink, IPG CarMaker, and dSPACE Automotive Simulation Models.

[0059] In the optional technical solutions provided in steps S3111 to S3114 above, the fuel economy parameters may include, but are not limited to: fuel consumption per 100 kilometers, cruising range per 100 kilometers, carbon emissions (the mass of carbon dioxide emitted per kilometer of driving), and energy efficiency ratio (the ratio of energy output to energy input). In the technical solution provided by the present invention, the target operating condition characteristic parameters may include: average vehicle speed, average driving speed, average acceleration, average deceleration, and idling time. The first duration may be a time length (e.g., 150s) pre-set by a technician based on the clustering requirements of the operating condition segments and the accuracy requirements of the operating condition prediction results.

[0060] In the technical solution provided by the present invention, the driving speed of the hybrid vehicle at time t is recorded as v(t), the acceleration is recorded as a(t), and the deceleration is recorded as b(t). The first duration of the i-th operating condition segment is 150s, and the sum of the time when the vehicle speed is 0 in the operating condition segment is recorded as t0. Therefore, the average vehicle speed of the operating condition segment is recorded as V1, the average driving speed is recorded as V2, the average acceleration is recorded as A1, the average deceleration is recorded as B1, and the idling time is recorded as K1, which can be shown as the following formulas (1) to (5) respectively:

[0061] In the above formula (2), j is the time period in which the vehicle speed is non-zero in the i-th operating condition segment, and satisfies t0+j=150.

[0062] In an optional embodiment, in step S312, determining the current driving condition from a plurality of candidate driving conditions based on the real-time driving data, and determining the current driving condition category from a plurality of driving condition categories include:

[0063] Step S3121, performing feature extraction on the real-time driving data according to the target operating condition characteristic parameters to obtain an extraction result;

[0064] Step S3122, performing fuzzy recognition on the extraction result to obtain a recognition result;

[0065] Step S3123 , comparing and matching the recognition result with the driving condition standard library, determining the current driving condition from multiple candidate driving conditions, and determining the current condition category from multiple condition categories.

[0066] The above method will be further described below with reference to FIG4 .

[0067] FIG4 is a schematic diagram of an optional hybrid vehicle driving condition construction process according to an embodiment of the present invention. As shown in FIG4 , first, raw vehicle data (including the aforementioned sample driving condition set and historical driving data) is collected, and the raw data is filtered and integrated (e.g., invalid data and abnormal data are eliminated). Next, driving condition characteristic parameters are selected and target driving condition characteristic parameters are determined. The raw data after the aforementioned filtering and integration processing is then divided into multiple driving condition segments (each driving condition segment can be used to characterize the change of the vehicle speed curve over a period of time). Furthermore, a cluster analysis is performed on the multiple driving condition segments to cluster driving condition segments belonging to the same or similar driving condition categories. Then, from the clustering results of each driving condition category, representative driving condition segments of that driving condition category are selected to form a driving condition segment-to-driving condition category mapping table. Furthermore, the driving condition segment-to-driving condition category mapping table is used as a standard driving condition library for the hybrid vehicle and stored in the vehicle controller control strategy model, thereby constructing four types of driving condition databases, including: a congestion driving condition database, an urban driving condition database, a suburban driving condition database, and a highway driving condition database.

[0068] In the technical solution provided by the present invention, as an optional implementation method, the real-time operating parameters of the hybrid vehicle can be collected by using an on-board information terminal. According to a preset time period (such as 20 seconds), the operating condition characteristic parameters in the real-time stored driving condition database are extracted, and then a fuzzy recognition method is used to match and compare the real-time driving condition of the hybrid vehicle with the operating condition input in the driving condition database to identify the operating condition category corresponding to the real-time driving condition. Furthermore, the operating condition category corresponding to the real-time driving condition can be used to predict the driving condition in the next time period.

[0069] In the technical solution provided by the present invention, as another optional implementation method, the on-board terminal obtains the real-time driving data of the vehicle from the controller local area network bus of the hybrid vehicle, transmits the real-time driving data to a remote computer via a wireless network and stores it in a database. The vehicle controller reads the real-time driving data of the hybrid vehicle from the database, and then uses the real-time driving data of the current time period to predict the driving conditions of the next time period.

[0070] In an optional embodiment, in step S33, using the operating condition prediction result and the current battery power of the hybrid vehicle, determining the target energy control strategy corresponding to the current operating mode includes:

[0071] Step S331, determining the current operating mode using the operating condition prediction result, the current battery charge, and the current driving data of the hybrid vehicle, wherein the operating condition prediction result includes at least: the predicted operating condition type and the predicted operating condition duration, and the current driving data includes at least: the accelerator pedal opening and the brake pedal opening;

[0072] Step S332: Select a target energy control strategy from a plurality of candidate energy control strategies according to the current operation mode.

[0073] The above method will be further described below with reference to FIG5 and FIG6 .

[0074] FIG5 is a schematic diagram of an optional energy control process of a hybrid vehicle according to an embodiment of the present invention. As shown in FIG5 , as an optional implementation method, the navigation system is used to obtain current travel planning information and road condition prediction information, and combined with the big data analysis technology in the cloud platform, the future driving conditions of the hybrid vehicle are predicted. In addition, based on the above-mentioned four types of driving condition databases, the categories of future driving conditions and the corresponding driving condition duration of each condition category are predicted. Furthermore, based on the current power level and operating mode of the hybrid vehicle's power battery, a target control strategy is determined to perform energy management on the hybrid vehicle.

[0075] Still as shown in Figure 5, specifically, the optimal power path for the hybrid vehicle is planned based on the economic energy consumption data fed back during vehicle control. Furthermore, the vehicle's future driving conditions are predicted through self-learning based on the characteristics of the four driving condition databases. Furthermore, based on the predicted future driving conditions, the vehicle is controlled. Specifically, the target operating mode of the hybrid vehicle is called, which can be, but is not limited to, one of the following: pure electric mode, engine mode, energy recovery mode, or hybrid power mode. A mode control strategy corresponding to the target operating mode is determined, and control instructions are sent to the hybrid vehicle, which is then controlled to execute the control instructions.

[0076] FIG6 is a flow chart of an optional energy control process of a hybrid vehicle according to an embodiment of the present invention. As shown in FIG6 , during the driving process of the hybrid vehicle, the real-time braking torque of the vehicle is obtained. When the real-time braking torque is greater than zero, the hybrid vehicle is controlled to enter the braking energy recovery mode. When the real-time braking torque is zero, it is determined whether the real-time speed of the hybrid vehicle is greater than zero. Further, when the real-time speed is zero, the hybrid vehicle is controlled to stop. When the real-time speed is greater than zero, the accelerator pedal travel is greater than a preset opening (such as 85%), and the required torque is greater than the maximum torque of the motor, the vehicle is controlled to enter the rapid acceleration mode. When the accelerator pedal travel and the required torque do not meet the aforementioned conditions, when the current charge of the hybrid vehicle is greater than the hybrid mode When the lower limit of the battery power and the real-time vehicle speed are greater than the speed threshold of the pure electric mode, the vehicle is controlled to enter the engine operation mode; when the current battery power of the hybrid vehicle is greater than the lower limit of the battery power of the hybrid mode and the real-time vehicle speed is less than the speed threshold of the pure electric mode, the hybrid vehicle is controlled to enter the pure electric mode; when the current battery power of the hybrid vehicle is less than the lower limit of the battery power of the hybrid mode and the real-time vehicle speed is less than the speed threshold of the pure electric mode, the vehicle is controlled to enter the engine mode, at this time, the engine is started to charge the vehicle's power battery; in the engine mode, when the required torque is greater than the engine economic torque, the hybrid vehicle is controlled to enter the hybrid drive mode, and when the required torque is less than or equal to the engine economic torque, the hybrid vehicle is controlled to enter the driving charging mode.

[0077] In an optional embodiment, in step S34, real-time regulation of the engine output power and the drive motor output power of the hybrid vehicle according to the target energy regulation strategy includes:

[0078] Step S341, determining the target value of the engine torque and the target value of the drive motor torque by using the target energy control strategy;

[0079] Step S342, determining a first target power according to the target value of the engine torque, and determining a second target power according to the target value of the drive motor torque;

[0080] Step S343 , controlling the hybrid vehicle to adjust the engine output power to the first target power, and adjusting the drive motor output power to the second target power.

[0081] In the optional technical solutions provided by the above steps S341 to S343, the above-mentioned engine torque target value can be determined based on the required torque, the engine torque upper limit value, and the speed; the above-mentioned drive motor torque target value can be determined based on the required torque, the engine torque upper limit value, and the real-time drive torque of the engine; the above-mentioned first target power is the target output power of the engine; and the above-mentioned second target power is the target output power of the drive motor.

[0082] In an optional embodiment, in step S34, when the current operating mode is the driving charging operating mode, the target energy control strategy is the driving charging torque distribution strategy, and determining the target engine torque value and the target drive motor torque value using the target energy control strategy includes:

[0083] Step S3411: In response to the hybrid vehicle's transmission input-end demand torque being less than or equal to a torque economy lower limit, determining, based on the driving and charging torque distribution strategy, an engine torque target value as a torque economy lower limit, wherein the torque economy lower limit is determined by a preset lower limit rule based on the engine speed and an engine economy parameter;

[0084] Step S3412: In response to the transmission input-end demand torque being greater than the torque economy lower limit and less than the torque economy upper limit, the engine torque target value is determined as the torque economy upper limit according to the driving charging torque distribution strategy. The torque economy upper limit is determined by a preset upper limit rule based on the engine speed and the engine economy parameter.

[0085] Step S3413: In response to the transmission input end required torque being greater than or equal to the torque economy upper limit, the engine torque target value is determined to be the transmission input end required torque according to the driving charging torque distribution strategy;

[0086] Step S3414: According to the driving charging torque distribution strategy, the target torque value of the driving motor is determined to be the difference between the required torque at the input end of the transmission and the target torque value of the engine.

[0087] The above method will be further described below with reference to FIG7 and FIG8 .

[0088] Figure 7 is a schematic diagram of an optional torque distribution control unit of a vehicle controller of a hybrid vehicle according to an embodiment of the present invention. As shown in Figure 7, as an optional implementation, the torque distribution control unit of the vehicle controller of the hybrid vehicle includes: pure electric mode, engine mode, driving charging mode, hybrid drive mode, rapid acceleration mode, and energy recovery mode.

[0089] FIG8 is a schematic diagram of an optional driving charging torque region division process according to an embodiment of the present invention. As shown in FIG8 , in the technical solution provided by the present invention, when the current operating mode of the hybrid vehicle is driving charging mode, at each speed, when the required torque of the transmission input shaft varies, the engine fuel consumption also varies. Based on the required torque of the transmission input shaft, Curve 1 is determined as the lower limit curve of the engine fuel consumption economic region, and Curve 2 is determined as the upper limit curve of the engine fuel consumption economic region. Furthermore, within the first quadrant of the speed-torque rectangular coordinate diagram, the region corresponding to the coordinate points whose ordinates are less than the coordinates of Curve 1 at the same horizontal coordinate is designated as Region E, the region corresponding to the coordinate points whose ordinates are greater than the coordinates of Curve 2 at the same horizontal coordinate is designated as Region G, and the region corresponding to the coordinate points whose ordinates are between Curves 1 and 2 at the same horizontal coordinate is designated as Region F. It should be noted that the required torque of the transmission input shaft can be a value calculated using data such as accelerator pedal opening and vehicle speed, or it can be a value obtained by first calculating the speed based on the vehicle speed and then determining it by querying a speed-required torque mapping table. It can also be understood that when the output torque of the engine is greater than zero and the power generation torque of the drive motor is less than zero, the sum of the two is the required torque of the gearbox input shaft.

[0090] Still as shown in Figure 8, the method of dividing the regions based on the required torque of the transmission input shaft can be: when the required torque of the transmission input shaft is less than the torque of curve 1, it is divided into region E; when the required torque of the transmission input shaft is greater than the torque of curve 1 and less than the torque of curve 2, it is divided into region F; when the required torque of the transmission input shaft is greater than the torque of curve 2, it is divided into region G.

[0091] Still as shown in FIG8 , further, in the driving charging mode, the vehicle controller performs torque distribution control based on the region in which the required torque of the transmission input shaft is located. Specifically, when the required torque of the transmission input shaft is in region E, to ensure the fuel economy of the hybrid vehicle, the vehicle controller executes the driving charging mode control strategy and controls the engine to operate along curve 1. At this time, the engine torque target value is the torque value of curve 1 (the lower limit of torque economy), and the drive motor torque target value is the difference between the required torque of the transmission input shaft and the engine torque target value. When the required torque of the transmission input shaft is in region F, to ensure the fuel economy of the hybrid vehicle, the vehicle controller executes the driving charging mode control strategy and controls the engine to operate along curve 2. At this time, the engine torque target value is the torque value of curve 2 (the upper limit of torque economy), and the drive motor torque target value is the difference between the required torque of the transmission input shaft and the engine torque target value. When the required torque of the transmission input shaft is in region G, to ensure the fuel economy of the hybrid vehicle, the engine torque target value is the required torque of the transmission input shaft, and the drive motor torque target value is zero.

[0092] In the technical solution provided by the present invention, it should also be noted that when the hybrid vehicle is in driving charging mode, in order to improve the stability of the driving power generation process, the change rate of the power generation torque of the drive motor can be reduced (for example, to -200N·m / s).

[0093] In an optional embodiment, in step S34, when the current operating mode is the hybrid drive operating mode, the target energy control strategy is a hybrid drive torque distribution strategy, and determining the target engine torque value and the target drive motor torque value using the target energy control strategy includes:

[0094] Step S3421: In response to the transmission input end demand torque of the hybrid vehicle being less than or equal to a first torque upper limit value, determining, according to the hybrid drive torque distribution strategy, an engine torque target value as the transmission input end demand torque, wherein the first torque upper limit value is determined by first engine characteristic information of the hybrid vehicle in the hybrid drive operating mode;

[0095] Step S3422: in response to the transmission input end required torque being greater than the first torque upper limit value, determining the engine torque target value to be the first torque upper limit value according to the hybrid drive torque distribution strategy;

[0096] Step S3423: According to the driving charging torque distribution strategy, the target torque value of the driving motor is determined to be the difference between the required torque at the input end of the transmission and the target torque value of the engine.

[0097] In the technical solution provided by the present invention, when the hybrid vehicle is in the hybrid drive mode, the vehicle controller performs torque distribution control based on the engine torque upper limit value (first torque upper limit value). Specifically: when the required torque of the transmission input shaft is less than or equal to the engine torque upper limit value, the engine torque target value is the required torque and the drive motor torque target value is zero; when the required torque of the transmission input shaft is greater than the engine torque upper limit value, the engine torque target value is the engine torque upper limit value, and the drive motor torque target value is the difference between the required torque and the engine torque upper limit value.

[0098] It should also be noted that in the technical solution provided by the present invention, when the hybrid vehicle is in hybrid drive mode, in order to improve the smooth operation of the hybrid vehicle, the rate of change of the power generation torque of the drive motor can be limited (for example, to 300 N·m / s), thereby avoiding the large change rate that impairs the drivability of the hybrid vehicle and improving the user experience.

[0099] In an optional embodiment, in step S34, when the current operating mode is the rapid acceleration operating mode, the target energy control strategy is the rapid acceleration torque distribution strategy, and determining the target engine torque value and the target drive motor torque value using the target energy control strategy includes:

[0100] Step S3431: In response to the transmission input end demand torque of the hybrid vehicle being less than or equal to a second torque upper limit value, determining, according to the rapid acceleration torque distribution strategy, an engine torque target value as the transmission input end demand torque, wherein the second torque upper limit value is determined by second engine characteristic information of the hybrid vehicle in a rapid acceleration operating mode;

[0101] Step S3432: in response to the transmission input end required torque being greater than the second torque upper limit value, determining the engine torque target value to be the second torque upper limit value according to the rapid acceleration torque distribution strategy;

[0102] In step S3433, according to the rapid acceleration torque distribution strategy, the target value of the drive motor torque is determined to be the difference between the required torque at the transmission input end and the actual value of the engine torque, wherein the actual value of the engine torque is collected in real time by the engine controller.

[0103] In the technical solution provided by the present invention, when the hybrid vehicle is in a rapid acceleration mode, the vehicle controller can be used to control the drive motor to provide a torque compensation value to meet the torque demand of the vehicle. Specifically: when the required torque of the transmission input shaft is less than or equal to the engine torque upper limit value, the engine torque target value is the required torque, and the drive motor torque target value is the difference between the required torque and the real-time drive torque of the engine; when the required torque of the transmission input shaft is greater than the engine torque upper limit value, the engine torque target value is the engine torque upper limit value, and the drive motor torque target value is the difference between the required torque and the real-time drive torque of the engine.

[0104] In the technical solution provided by the present invention, it should be noted that the vehicle controller can obtain the real-time driving torque of the engine from the engine control system through the controller local area network bus of the hybrid vehicle. It can be understood that the engine torque target value can be the torque value required to be output by the engine obtained by the vehicle controller based on the torque distribution control instruction, and the real-time driving torque of the engine can be the actual driving torque generated by the engine in response to the control instruction of the engine control system.

[0105] In the technical solution provided by the present invention, it should also be noted that when the hybrid vehicle is in rapid acceleration mode, in order to meet the power requirements of the hybrid vehicle, the rate of change of the power generation torque of the drive motor can be increased (for example, to 500 N·m / s).

[0106] The energy control method for hybrid vehicles provided by the present invention can achieve the following technical effects:

[0107] (1) Combining the real-time driving data of hybrid vehicles, a standard driving condition library, and road condition information, a driving condition database matching the hybrid vehicles is constructed after screening and integration, feature parameter extraction, segmentation, and fuzzy recognition. Based on the real-time driving conditions of the hybrid vehicles and the driving condition database, the future driving conditions of the hybrid vehicles are accurately predicted, thereby improving the accuracy of the prediction results, reducing the complexity of the prediction process, and improving the prediction efficiency.

[0108] (2) Based on the predicted results of the hybrid vehicle's future driving conditions, the current battery current, and the current operating mode, the target energy control strategy is selected, and then the target energy control strategy is used to distribute torque and control energy of the hybrid vehicle, thereby improving the fuel economy of the hybrid vehicle, reducing fuel consumption, and enhancing the user's driving experience.

[0109] In this embodiment, a hybrid vehicle energy control device is also provided. This device is configured to implement the above-mentioned embodiments and preferred embodiments. Details already described are omitted for clarity. As used below, a "module" refers to a combination of software and / or hardware that can implement a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.

[0110] FIG9 is a structural block diagram of an energy control device for a hybrid vehicle according to an embodiment of the present invention. As shown in FIG9 , the device includes:

[0111] A first determining module 901 is configured to determine a current driving condition and a current driving condition category based on real-time driving data corresponding to the hybrid vehicle and a driving condition standard library;

[0112] The prediction module 902 is configured to predict the driving condition of the hybrid vehicle based on the current driving condition, the current driving condition category, and road condition information to obtain a driving condition prediction result, wherein the road condition information includes at least one of the following: real-time road condition data and predicted road condition data;

[0113] a second determining module 903 configured to determine a target energy control strategy corresponding to a current operating mode of the hybrid vehicle using the operating condition prediction result and a current battery charge corresponding to the hybrid vehicle, wherein the current operating mode is one of the following: a motor drive operating mode, an engine drive operating mode, a hybrid drive operating mode, a brake energy recovery operating mode, a driving charging operating mode, and a rapid acceleration operating mode;

[0114] The control module 904 is configured to control the engine output power and the drive motor output power of the hybrid vehicle in real time according to the target energy control strategy.

[0115] Optionally, the first determination module 901 is further configured to: determine the current driving condition and the current operating condition category based on the real-time driving data and the driving condition standard library corresponding to the hybrid vehicle, including: constructing a driving condition standard library using a sample operating condition set, historical driving data and target operating condition characteristic parameters corresponding to the hybrid vehicle, wherein the driving condition standard library includes multiple candidate driving conditions, and the multiple candidate driving conditions belong to multiple operating condition categories; determine the current driving condition from the multiple candidate driving conditions based on the real-time driving data, and determine the current operating condition category from the multiple operating condition categories.

[0116] Optionally, the first determination module 901 is further configured to: construct a driving condition standard library using a sample operating condition set, historical driving data, and target operating condition characteristic parameters corresponding to a hybrid vehicle, including: extracting features from the sample operating condition set to obtain a plurality of operating condition characteristic parameters, wherein the sample operating condition set includes: simulation test operating conditions and actual vehicle test operating conditions; using the fuel economy parameters corresponding to the hybrid vehicle as optimization indicators, performing orthogonal optimization analysis on the plurality of operating condition characteristic parameters, and selecting target operating condition characteristic parameters from the plurality of operating condition characteristic parameters; segmenting the historical driving data of the hybrid vehicle according to the first time length to obtain a plurality of operating condition segments; and performing cluster analysis on the plurality of operating condition segments based on the target operating condition characteristic parameters to generate a driving condition standard library.

[0117] Optionally, the above-mentioned first determination module 901 is also configured to: determine the current driving condition from multiple candidate driving conditions based on real-time driving data, and determine the current operating condition category from multiple operating condition categories, including: performing feature extraction on the real-time driving data according to the target operating condition characteristic parameters to obtain extraction results; performing fuzzy recognition on the extraction results to obtain recognition results; comparing and matching the recognition results with the driving condition standard library, determining the current driving condition from multiple candidate driving conditions, and determining the current operating condition category from multiple operating condition categories.

[0118] Optionally, the second determination module 903 is further configured to: determine the target energy control strategy corresponding to the current operating mode using the operating condition prediction result and the current battery power corresponding to the hybrid vehicle, including: determining the current operating mode using the operating condition prediction result, the current battery power and the current driving data of the hybrid vehicle, wherein the operating condition prediction result includes at least: the predicted operating condition category, the predicted operating condition duration, and the current driving data includes at least: the accelerator pedal opening, the brake pedal opening; and selecting the target control strategy from multiple candidate energy control strategies according to the current operating mode.

[0119] Optionally, the above-mentioned control module 904 is further configured to: perform real-time control of the engine output power and the drive motor output power of the hybrid vehicle according to the target energy control strategy, including: determining the engine torque target value and the drive motor torque target value using the target energy control strategy; determining a first target power according to the engine torque target value, and determining a second target power according to the drive motor torque target value; controlling the hybrid vehicle to adjust the engine output power to the first target power, and adjusting the drive motor output power to the second target power.

[0120] Optionally, the control module 904 is further configured to: when the current operating mode is the driving charging operating mode, the target energy control strategy is the driving charging torque distribution strategy, and determining the target engine torque value and the target drive motor torque value using the target energy control strategy includes: in response to the transmission input end demand torque of the hybrid vehicle being less than or equal to the torque economy lower limit value, determining the target engine torque value as the torque economy lower limit value according to the driving charging torque distribution strategy, wherein the torque economy lower limit value is determined by a preset lower limit rule of the engine speed and the engine economy parameter; in response to the transmission input end demand torque being greater than the torque economy lower limit value and less than the torque economy upper limit value, determining the target engine torque value as the torque economy upper limit value according to the driving charging torque distribution strategy, wherein the torque economy upper limit value is determined by a preset upper limit rule of the engine speed and the engine economy parameter; in response to the transmission input end demand torque being greater than or equal to the torque economy upper limit value, determining the target engine torque value as the transmission input end demand torque according to the driving charging torque distribution strategy; and determining the target drive motor torque value as the difference between the transmission input end demand torque and the target engine torque value according to the driving charging torque distribution strategy.

[0121] Optionally, the control module 904 is further configured to: when the current operating mode is the hybrid drive operating mode, the target energy control strategy is a hybrid drive torque distribution strategy, and determining the target engine torque value and the target drive motor torque value using the target energy control strategy includes: in response to the required torque at the transmission input end of the hybrid vehicle being less than or equal to a first torque upper limit value, determining the target engine torque value as the required torque at the transmission input end according to the hybrid drive torque distribution strategy, wherein the first torque upper limit value is determined by first engine characteristic information of the hybrid vehicle in the hybrid drive operating mode; in response to the required torque at the transmission input end being greater than the first torque upper limit value, determining the target engine torque value as the first torque upper limit value according to the hybrid drive torque distribution strategy; and determining the target drive motor torque value as the difference between the required torque at the transmission input end and the target engine torque value according to the driving charging torque distribution strategy.

[0122] Optionally, the control module 904 is further configured to: when the current operating mode is the rapid acceleration operating mode, the target energy control strategy is the rapid acceleration torque distribution strategy, and the target energy control strategy is used to determine the target engine torque value and the target drive motor torque value, including: in response to the required torque at the transmission input end of the hybrid vehicle being less than or equal to the second torque upper limit value, determining the target engine torque value as the required torque at the transmission input end according to the rapid acceleration torque distribution strategy, wherein the second torque upper limit value is determined by the second engine characteristic information of the hybrid vehicle in the rapid acceleration operating mode; in response to the required torque at the transmission input end being greater than the second torque upper limit value, determining the target engine torque value as the second torque upper limit value according to the rapid acceleration torque distribution strategy; and determining the target drive motor torque value as the difference between the required torque at the transmission input end and the actual value of the engine torque according to the rapid acceleration torque distribution strategy, wherein the actual value of the engine torque is collected in real time by the engine controller.

[0123] It should be noted that the above modules can be implemented through software or hardware. For the latter, it can be implemented in the following ways, but not limited to: the above modules are all located in the same processor; or the above modules are located in different processors in any combination.

[0124] According to another aspect of an embodiment of the present invention, a vehicle is provided, comprising an on-board memory and an on-board processor, wherein a computer program is stored in the on-board memory, and the on-board processor is configured to run the computer program to execute any one of the aforementioned energy control methods for a hybrid vehicle.

[0125] Optionally, in this embodiment, the vehicle-mounted memory may be configured to store a computer program configured to perform the following steps:

[0126] Step S1, determining a current driving condition and a current driving condition category based on real-time driving data corresponding to the hybrid vehicle and a driving condition standard library;

[0127] Step S2, predicting the driving condition of the hybrid vehicle based on the current driving condition, the current driving condition category, and road condition information to obtain a driving condition prediction result, wherein the road condition information includes at least one of the following: real-time road condition data and predicted road condition data;

[0128] Step S3, using the operating condition prediction result and the current battery charge of the hybrid vehicle, determining a target energy control strategy corresponding to the current operating mode of the hybrid vehicle, wherein the current operating mode is one of the following: motor drive operating mode, engine drive operating mode, hybrid drive operating mode, brake energy recovery operating mode, driving charging operating mode, and rapid acceleration operating mode;

[0129] Step S4: Real-time control of the engine output power and the drive motor output power of the hybrid vehicle according to the target energy control strategy.

[0130] Optionally, in this embodiment, the above-mentioned storage medium may include but is not limited to: a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and other media that can store computer programs.

[0131] Optionally, in this embodiment, the vehicle-mounted processor may be configured to execute the following steps via a computer program:

[0132] Step S1, determining a current driving condition and a current driving condition category based on real-time driving data corresponding to the hybrid vehicle and a driving condition standard library;

[0133] Step S2, predicting the driving condition of the hybrid vehicle based on the current driving condition, the current driving condition category, and road condition information to obtain a driving condition prediction result, wherein the road condition information includes at least one of the following: real-time road condition data and predicted road condition data;

[0134] Step S3, using the operating condition prediction result and the current battery charge of the hybrid vehicle, determining a target energy control strategy corresponding to the current operating mode of the hybrid vehicle, wherein the current operating mode is one of the following: motor drive operating mode, engine drive operating mode, hybrid drive operating mode, brake energy recovery operating mode, driving charging operating mode, and rapid acceleration operating mode;

[0135] Step S4: Real-time control of the engine output power and the drive motor output power of the hybrid vehicle according to the target energy control strategy.

[0136] Optionally, specific examples in this embodiment may refer to the examples described in the above embodiment and its optional implementation manners, and this embodiment will not be described in detail here.

[0137] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0138] In the above embodiments of the present invention, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0139] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0140] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0141] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0142] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a read-only memory, a random access memory, a mobile hard disk, a magnetic disk or an optical disk.

[0143] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A method for controlling energy of a hybrid vehicle, comprising: Determine the current driving condition and the current condition category based on the real-time driving data and driving condition standard library corresponding to the hybrid vehicle; Based on the current driving condition, the current condition category and the road condition information, a driving condition prediction is performed on the hybrid vehicle to obtain a condition prediction result, wherein the road condition information includes at least one of the following: real-time road condition data and predicted road condition data; Determining a target energy control strategy corresponding to a current operating mode of the hybrid vehicle by using the operating condition prediction result and the current battery power corresponding to the hybrid vehicle, wherein the current operating mode is one of the following: a motor drive operating mode, an engine drive operating mode, a hybrid drive operating mode, a brake energy recovery operating mode, a driving charging operating mode, and a rapid acceleration operating mode; The engine output power and the drive motor output power of the hybrid vehicle are regulated in real time according to the target energy regulation strategy.

2. The energy control method for a hybrid vehicle according to claim 1, wherein: Determining the current driving condition and the current condition category based on the real-time driving data corresponding to the hybrid vehicle and the driving condition standard library includes: Using the sample operating condition set, historical driving data and target operating condition characteristic parameters corresponding to the hybrid vehicle, constructing the driving condition standard library, wherein the driving condition standard library includes a plurality of candidate driving conditions, and the plurality of candidate driving conditions belong to a plurality of operating condition categories; Based on the real-time driving data, a current driving condition is determined from the plurality of candidate driving conditions, and a current operating condition category is determined from the plurality of operating condition categories.

3. The energy control method for a hybrid vehicle according to claim 2, wherein: Using the sample operating condition set corresponding to the hybrid vehicle, the historical driving data and the target operating condition characteristic parameters, constructing the driving condition standard library includes: Extracting features from the sample operating condition set to obtain a plurality of operating condition feature parameters, wherein the sample operating condition set includes: a simulation test operating condition and a real vehicle test operating condition; Taking the fuel economy parameter corresponding to the hybrid vehicle as an optimization index, performing orthogonal optimization analysis on the multiple operating condition characteristic parameters, and selecting a target operating condition characteristic parameter from the multiple operating condition characteristic parameters; Dividing the historical driving data of the hybrid vehicle into segments according to the first time length to obtain a plurality of operating condition segments; A cluster analysis is performed on the multiple operating condition segments based on the target operating condition characteristic parameters to generate a driving condition standard library.

4. The energy control method for a hybrid vehicle according to claim 2, wherein: Based on the real-time driving data, determining the current driving condition from the plurality of candidate driving conditions, and determining the current condition category from the plurality of condition categories comprises: According to the target operating condition characteristic parameters, feature extraction is performed on the real-time driving data to obtain an extraction result; Performing fuzzy recognition on the extraction result to obtain a recognition result; The recognition result is compared and matched with the driving condition standard library, a current driving condition is determined from the multiple candidate driving conditions, and a current condition category is determined from the multiple condition categories.

5. The energy control method for a hybrid vehicle according to claim 1, wherein: Determining the target energy control strategy corresponding to the current operating mode by using the operating condition prediction result and the current battery power corresponding to the hybrid vehicle includes: Determining the current operating mode using the operating condition prediction result, the current battery power and the current driving data of the hybrid vehicle, wherein the operating condition prediction result at least includes: a predicted operating condition category and a predicted operating condition duration, and the current driving data at least includes: an accelerator pedal opening and a brake pedal opening; According to the current operation mode, a target control strategy is selected from a plurality of candidate energy control strategies.

6. The energy control method for a hybrid vehicle according to claim 1, wherein: The real-time regulation of the engine output power and the drive motor output power of the hybrid vehicle according to the target energy regulation strategy includes: Determining the target value of the engine torque and the target value of the drive motor torque by using the target energy control strategy; Determine a first target power according to the engine torque target value, and determine a second target power according to the drive motor torque target value; The hybrid vehicle is controlled to adjust the engine output power to the first target power, and to adjust the drive motor output power to the second target power.

7. The energy control method for a hybrid vehicle according to claim 6, wherein: When the current operation mode is the driving charging operation mode, the target energy control strategy is a driving charging torque distribution strategy, and using the target energy control strategy to determine the target engine torque value and the target drive motor torque value includes: In response to the required torque of the transmission input end of the hybrid vehicle being less than or equal to the torque economy lower limit value, according to the driving charging torque distribution strategy, determining the engine torque target value to be the torque economy lower limit value, wherein the torque economy lower limit value is determined by a preset lower limit rule of an engine speed and an engine economy parameter; In response to the required torque at the input end of the transmission being greater than the torque economy lower limit value and less than the torque economy upper limit value, according to the driving charging torque distribution strategy, determining the engine torque target value as the torque economy upper limit value, wherein the torque economy upper limit value is determined by a preset upper limit rule of the engine speed and the engine economy parameter; In response to the transmission input end required torque being greater than or equal to the torque economy upper limit value, determining the engine torque target value to be the transmission input end required torque according to the driving charging torque distribution strategy; According to the driving charging torque distribution strategy, the drive motor torque target value is determined as the difference between the required torque at the input end of the transmission and the engine torque target value.

8. The energy control method for a hybrid vehicle according to claim 6, wherein: When the current operation mode is the hybrid drive operation mode, the target energy control strategy is a hybrid drive torque distribution strategy, and using the target energy control strategy to determine the target engine torque value and the target drive motor torque value includes: In response to the transmission input end required torque of the hybrid vehicle being less than or equal to a first torque upper limit value, determining the engine torque target value to be the transmission input end required torque according to the hybrid drive torque distribution strategy, wherein the first torque upper limit value is determined by first engine characteristic information of the hybrid vehicle in the hybrid drive operation mode; In response to the required torque at the input end of the transmission being greater than the first torque upper limit value, determining the engine torque target value to be the first torque upper limit value according to the hybrid drive torque distribution strategy; According to the driving charging torque distribution strategy, the drive motor torque target value is determined as the difference between the required torque at the input end of the transmission and the engine torque target value.

9. The energy control method for a hybrid vehicle according to claim 6, wherein: When the current operation mode is the rapid acceleration operation mode, the target energy control strategy is a rapid acceleration torque distribution strategy, and using the target energy control strategy to determine the target engine torque value and the target drive motor torque value includes: In response to the transmission input end required torque of the hybrid vehicle being less than or equal to the second torque upper limit value, the engine torque target value is determined to be the transmission input end required torque according to the rapid acceleration torque distribution strategy, wherein the second torque upper limit value is determined by the hybrid vehicle in the rapid acceleration operation mode. The second engine characteristic information is determined; In response to the required torque at the input end of the transmission being greater than the second torque upper limit value, determining the engine torque target value to be the second torque upper limit value according to the rapid acceleration torque distribution strategy; According to the rapid acceleration torque distribution strategy, the drive motor torque target value is determined as the difference between the required torque at the transmission input end and the actual value of the engine torque, wherein the actual value of the engine torque is collected in real time by the engine controller.

10. A vehicle, comprising an on-board memory and an on-board processor, wherein the on-board memory stores a computer program, and the on-board processor is configured to run the computer program to execute the energy control method of the hybrid vehicle according to any one of claims 1 to 9.

Images