Mode control method, device, equipment, medium and product

Abstract

The invention discloses a mode control method, device and equipment, a medium and a product. The method comprises the steps that operation parameters of a target vehicle are obtained, and the current operation condition is determined according to the operation parameters; the battery state of the target vehicle is obtained, and a target operation mode is determined according to the current operation working condition and the battery state; and based on an S-shaped curve transition strategy, the target vehicle is controlled to be switched to operate in the target operation mode. According to the technical scheme, intelligent operation mode management of the vehicle under the complex working condition can be achieved, and smooth mode switching and optimal energy utilization are achieved on the premise that the power performance is guaranteed.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of new energy vehicle control technology, and in particular to a mode control method, device, equipment, medium and product. Background Technology

[0002] With the accelerated electrification of commercial vehicles, range-extended electric vehicles (REEVs) have become an important technological route for commercial vehicle electrification due to their advantages such as long driving range and convenient refueling. REEVs use range extenders to recharge the battery, achieving the characteristic of "electric drive, gasoline range." However, how to intelligently manage vehicle operating modes according to actual working conditions and optimize energy management strategies has become a key technical challenge in improving the economy and power of REEVs. Summary of the Invention

[0003] This invention provides a mode control method, device, equipment, medium, and product to enable intelligent operation mode management of vehicles under complex working conditions, achieving smooth mode switching and optimal energy utilization while ensuring power performance.

[0004] According to one aspect of the present invention, a mode control method is provided, comprising:

[0005] Obtain the operating parameters of the target vehicle, and determine the current operating condition based on the operating parameters;

[0006] Obtain the battery status of the target vehicle, and determine the target operating mode based on the current operating conditions and the battery status;

[0007] Based on the S-curve transition strategy, the target vehicle is controlled to switch to the target operating mode.

[0008] In some embodiments of the present invention, determining the current operating condition based on the operating parameters includes:

[0009] The operating parameters are subjected to feature extraction to obtain an operating feature vector;

[0010] Based on the operating condition scoring function, the score corresponding to each type of operating condition is determined according to the operating feature vector;

[0011] The current operating condition is determined based on the score and confidence threshold corresponding to each type of operating condition.

[0012] In some embodiments of the present invention, determining a target operating mode based on the current operating conditions and the battery state includes:

[0013] Based on the current operating conditions and the battery status, a preset decision matrix is ​​queried to determine the target operating mode.

[0014] In some embodiments of the present invention, before controlling the target vehicle to switch to the target operating mode based on the S-curve transition strategy, the method further includes:

[0015] Obtain the switching timing strategy;

[0016] Generate an S-shaped curve.

[0017] In some embodiments of the present invention, generating an S-shaped curve includes:

[0018] Obtain the transition progress parameters, and construct an S-shaped transition factor function based on the transition progress parameters;

[0019] A power transition equation is constructed based on the S-shaped transition factor function; the power transition equation is: the actual power at the current moment is the product of the difference between the target power value and the initial power value, the sum of the target power value and the initial power value, and the S-shaped transition factor function.

[0020] The system acquires the power allocation strategy for mode switching, the power change rate limit, and the transition time; the power allocation strategy for mode switching includes: a pure electric mode switching to range-extended mode strategy and a range-extended mode switching to pure electric mode strategy.

[0021] In some embodiments of the present invention, the current operating conditions include: urban delivery conditions, highway transportation conditions, mountain transportation conditions, heavy-load uphill conditions, and idling waiting conditions;

[0022] The target operating modes include: pure electric mode, range-extended charging mode, load following mode, power following mode, and fail-safe mode.

[0023] According to another aspect of the present invention, a mode control device is provided, the device comprising:

[0024] The first processing module is used to acquire the operating parameters of the target vehicle and determine the current operating condition based on the operating parameters;

[0025] The second processing module is used to obtain the battery status of the target vehicle and determine the target operating mode based on the current operating conditions and the battery status.

[0026] The control module is used to control the target vehicle to switch to the target operating mode based on the S-curve transition strategy.

[0027] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0028] At least one processor; and

[0029] A memory communicatively connected to the at least one processor; wherein,

[0030] The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the mode control method according to any embodiment of the present invention.

[0031] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the mode control method described in any embodiment of the present invention.

[0032] According to another aspect of the present invention, embodiments of the present invention also provide a computer program product, the computer program product including a computer program, which, when executed by a processor, implements the mode control method described in any embodiment of the present invention.

[0033] This invention first acquires the operating parameters of the target vehicle and determines the current operating condition based on these parameters. Then, it acquires the battery status of the target vehicle and determines the target operating mode based on the current operating condition and battery status. Finally, based on an S-curve transition strategy, it controls the target vehicle to switch to the target operating mode. Through this invention, intelligent operating mode management of vehicles under complex operating conditions can be achieved, ensuring smooth mode switching and optimal energy utilization while maintaining power performance.

[0034] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0035] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 This is a flowchart of a mode control method according to an embodiment of the present invention;

[0037] Figure 2 This is a schematic diagram of the structure of a mode control device according to an embodiment of the present invention;

[0038] Figure 3 This is a schematic diagram of the structure of an electronic device that implements the mode control method of the present invention. Detailed Implementation

[0039] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0040] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and their derivatives, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0041] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0042] Example 1

[0043] Figure 1 This is a flowchart of a mode control method according to an embodiment of the present invention. This embodiment is applicable to the operation mode control of range-extended vehicles. The method can be executed by the mode control device in this embodiment, which can be implemented in software and / or hardware, such as... Figure 1 As shown, the method specifically includes the following steps:

[0044] S101. Obtain the operating parameters of the target vehicle and determine the current operating conditions based on the operating parameters.

[0045] In this embodiment, the target vehicle can be a range-extended commercial vehicle. It is known that a range-extended commercial vehicle (RECV) is a hybrid commercial vehicle that combines pure electric drive with a gasoline (or gas) range extender. In urban driving conditions, this type of vehicle primarily relies on the battery pack for power, achieving zero-emission operation. However, during long-distance travel or when the battery is low, the range extender activates to charge the battery, thereby extending the vehicle's driving range.

[0046] It should be noted that the operating parameters of the target vehicle can be parameters such as vehicle speed, load, and ambient temperature during the operation of the range-extended commercial vehicle. The current operating condition can be the operating condition that the range-extended commercial vehicle is currently in.

[0047] Optionally, the current operating conditions include: urban delivery (frequent starts and stops, average speed <40km / h, frequent load changes), highway transportation (continuous high speed, average speed >60km / h, stable load), mountain transportation (large gradient changes, average gradient >3%, large power demand fluctuations), heavy-load climbing (load rate >80% and gradient >5%, duration >30s), and idling waiting (vehicle speed = 0, extremely low power demand).

[0048] Specifically, real-time vehicle operating parameters are collected, including: vehicle speed signal (sampling period 20ms), driver power demand (sampling period 20ms), road gradient (sampling period 200ms), vehicle load (sampling period 1000ms), range extender status (sampling period 50ms), and ambient temperature (sampling period 1000ms), etc. The collected signals are filtered and outlier processed to ensure data reliability. Then, a working condition identification algorithm based on multi-feature fusion and multi-dimensional feature weighted scoring accurately identifies the current operating condition by constructing a working condition feature vector and a scoring function.

[0049] S102. Obtain the battery status of the target vehicle and determine the target operating mode based on the current operating conditions and battery status.

[0050] Among them, the battery status can be the power battery's SOC (State of Charge), which refers to the remaining battery capacity, usually expressed as a percentage.

[0051] It should be noted that the target operating mode can be the operating mode that the vehicle should switch to based on the current conditions.

[0052] Optional target operating modes include: pure electric mode (EV, short for Electric Vehicle Mode, powered only by the battery, with the range extender off), range-extended charging mode (REx-CHG, short for Range-Extended Charging Mode, where the range extender generates electricity and charges at its optimal efficiency point), load following mode (REx-LF, short for Range-Extended Load Following Mode, where the range extender output follows the average load), power following mode (REx-PF, short for Range-Extended Power Following Mode, where the range extender output follows real-time power demand), and fail-safe mode (SAFE, short for Safe Mode, system fault protection mode).

[0053] Specifically, the SOC of the power battery can be collected based on a sampling period of 100ms, and then the optimal operating mode can be determined based on the identified operating conditions, SOC status and power requirements.

[0054] S103. Based on the S-curve transition strategy, control the target vehicle to switch to the target operating mode.

[0055] It is known that the S-curve transition strategy ensures that the changes in power or control variables are smooth during mode switching by designing a smooth transition function, thus avoiding shocks or discomfort caused by abrupt changes.

[0056] Specifically, an S-shaped curve transition strategy is adopted to achieve smooth switching between modes and control the target vehicle to switch to the target operating mode.

[0057] This invention first acquires the operating parameters of the target vehicle and determines the current operating condition based on these parameters. Then, it acquires the battery status of the target vehicle and determines the target operating mode based on the current operating condition and battery status. Finally, based on an S-curve transition strategy, it controls the target vehicle to switch to the target operating mode. Through this invention, intelligent operating mode management of vehicles under complex operating conditions can be achieved, ensuring smooth mode switching and optimal energy utilization while maintaining power performance.

[0058] Optionally, the current operating condition can be determined based on operating parameters, including:

[0059] Feature extraction is performed on the running parameters to obtain the running feature vector.

[0060] In the specific implementation process, the features for extracting operating parameters can include: speed features (average vehicle speed, speed standard deviation, mean acceleration, etc.), power features (average power demand, power fluctuation rate, peak power, etc.), terrain features (average slope, slope change rate, cumulative elevation gain, etc.), and load features (current load rate, load change frequency, etc.).

[0061] Specifically, define the vehicle operation feature vector. where n can be 12:

[0062] Velocity characteristics (The ratio of average speed to maximum speed, normalized average speed).

[0063] Parking frequency characteristics (Ratio of parking times to time; number of parking times per unit of time).

[0064] Load variation characteristics (Ratio of standard deviation of load capacity to rated load capacity);

[0065] Velocity stability characteristics (1 - the ratio of the standard deviation of velocity to the average velocity, and the complement of the coefficient of variation of velocity).

[0066] High-speed ratio characteristics (The ratio of high-speed driving time to total driving time; the percentage of high-speed driving time).

[0067] Load stability characteristics (1 - the ratio of the absolute value of the weight change to the rated load, and the complement of the load change rate).

[0068] Slope characteristics (The ratio of average slope to maximum slope, normalized value of average slope).

[0069] High degree of variation characteristics (Ratio of altitude change to reference altitude, normalized cumulative altitude change).

[0070] Power fluctuation characteristics (The ratio of power standard deviation to average power, power coefficient of variation).

[0071] Load capacity characteristics (Ratio of current load to rated load, current load factor);

[0072] Slope characteristics (Ratio of current slope to maximum slope, normalized value of current slope);

[0073] Duration characteristics (The ratio of duration to reference time, normalized duration value).

[0074] Based on the operating condition scoring function, the score corresponding to each type of operating condition is determined according to the operating feature vector.

[0075] In the specific implementation process, for each working condition type i∈{urban delivery, highway transportation, mountain transportation, heavy-load uphill climbing, idling waiting}, the working condition scoring function is defined as follows: ;

[0076] in, Let be the weight coefficient of the i-th working condition for the j-th feature, satisfying:

[0077] (Weight normalization constraint);

[0078] 0≤ ≤1 (weight range);

[0079] Specific weight matrix Obtained through expert experience and data calibration.

[0080] In practice, to eliminate the influence of different scoring dimensions, the maximum value normalization method is adopted:

[0081] .

[0082] The current operating condition is determined based on the score and confidence threshold corresponding to each type of operating condition.

[0083] Specifically, the final operating condition type is determined by the following criteria:

[0084] , ;

[0085] , ;

[0086] in, This is the confidence threshold, typically set to 0.7.

[0087] The operating condition recognition method in this invention is based on the weighted distance classifier principle in pattern recognition theory. The vehicle's operating state is mapped to a high-dimensional feature space, and operating condition classification is achieved by calculating the weighted similarity between the current state and each standard operating condition mode.

[0088] Let the standard operating condition mode set be If the current vehicle status is X, then the recognition process can be represented as: ;

[0089] in, The weighted Euclidean distance from the current state to the i-th standard working condition. Let j be the j-th feature value of the current state. It is the j-th characteristic standard value of the i-th standard working condition.

[0090] The working condition identification result is as follows: .

[0091] Preferably, to improve recognition accuracy, embodiments of the present invention introduce a gradient descent-based adaptive weight optimization mechanism: ;

[0092] in, Let L be the learning rate and L be the loss function, defined as: , For the true working condition label of the k-th sample, The results are for identification.

[0093] Optionally, the target operating mode can be determined based on the current operating conditions and battery status, including:

[0094] Based on the current operating conditions and battery status, the system queries the preset decision matrix to determine the target operating mode.

[0095] In this embodiment, the preset decision matrix can be as shown in Table 1:

[0096] Table 1

[0097]

[0098] Specifically, based on the operating condition type and SOC range, a preset decision matrix is ​​queried to determine the target operating mode.

[0099] In actual operation, this embodiment determines the optimal operating mode based on the identified operating conditions, SOC status, and power requirements, and optimizes the mode switching trigger conditions: hysteresis control is introduced to avoid frequent mode switching; a minimum duration is set to prevent mode jitter; and switching costs are considered to optimize the switching timing.

[0100] Optionally, before controlling the target vehicle to switch to the target operating mode based on the S-curve transition strategy, the following steps are also included:

[0101] Get the switching timing strategy.

[0102] In this embodiment, a switching timing strategy is designed, namely:

[0103] T0: Identify the switching requirement and prepare for the switching;

[0104] T0+ΔT1: Adjust battery power limit, pre-compensate;

[0105] T0+ΔT2: Start / stop the range extender;

[0106] T0+ΔT3: S-shaped curve adjusts power distribution;

[0107] T0+ΔT4: Switching complete, entering the new mode.

[0108] Generate an S-shaped curve.

[0109] Specifically, this invention uses an S-shaped curve based on a cosine function to achieve smooth power transition, ensuring the continuity of power output during mode switching.

[0110] Optionally, generating an S-shaped curve includes:

[0111] Obtain the transition progress parameters and construct an S-shaped transition factor function based on the transition progress parameters.

[0112] Specifically, define the transition progress parameters:

[0113] ,in, .

[0114] S-shaped transition factor function:

[0115] The function satisfies: S(0)=0 (starting point), S(1)=1 (ending point). (The initial slope is zero) (The termination slope is zero).

[0116] The power transition equation is constructed based on the S-shaped transition factor function.

[0117] The power transition equation is: the actual power at the current moment is the product of the difference between the target power value and the initial power value, the sum of the target power value and the initial power value, and the S-shaped transition factor function.

[0118] Specifically, the total power transition equation can be expressed as:

[0119] ;

[0120] in: Indicates the initial power value. P(t) represents the target power value, and P(t) represents the actual power at time t.

[0121] Acquire mode switching power allocation strategy, power change rate limit, and transition time.

[0122] The mode switching power allocation strategies include: a pure electric mode switching to range-extended mode strategy and a range-extended mode switching to pure electric mode strategy.

[0123] Specifically, the mode switching power allocation strategy can be described as follows:

[0124] Scenario 1: Switching from pure electric mode to range extender mode (EV→REx):

[0125] Battery power variation:

[0126] ;

[0127] Range extender power variation:

[0128] ;

[0129] Power balance constraints:

[0130] .

[0131] Scenario 2: Switching from range extender mode to pure electric mode (REx→EV):

[0132] Range extender power variation:

[0133] ;

[0134] Battery power variation:

[0135] .

[0136] In actual operation, to ensure smooth switching, the power change rate limit should meet the following requirements: ;

[0137] in:

[0138] ;

[0139] Therefore, the maximum power change rate is:

[0140] .

[0141] In the specific implementation process, based on the power change rate limit, the minimum transition time is: ;

[0142] Actual transition time selection: ;

[0143] in The baseline transition time is 3 seconds, with a typical value of 3 seconds.

[0144] In practical control systems, discretization is used for implementation:

[0145] Time step: (Control cycle) Discrete time points: k=0,1,2,...,N where: ;

[0146] Discrete power calculation: ;

[0147] Power allocation execution: .

[0148] In the specific implementation process, control parameters can be adaptively optimized based on historical data and actual results. This can be described as follows: 1. Parameter learning: Record the smoothness index of each mode switch; statistically analyze energy consumption data under different operating conditions; analyze the frequency and duration of mode switching. 2. Parameter optimization: Adjust the weight coefficient for operating condition identification; optimize the mode switching threshold; update the transition time of the S-curve.

[0149] In the specific implementation process, the system status can also be monitored in real time to identify and handle anomalies: 1. Fault detection: range extender start failure detection, mode switching timeout detection, power output anomaly detection, communication fault detection; 2. Develop protection strategies: fault level assessment (minor / moderate / severe), degraded operation strategy (power limit / lock mode / safe shutdown), fault information recording and reporting.

[0150] The technical solution of this invention first achieves accurate identification of complex operating conditions for range-extended commercial vehicles based on a multi-dimensional feature fusion recognition algorithm that integrates speed, power, terrain, and load. Then, it achieves intelligent selection of operating modes based on a two-dimensional decision matrix of operating condition type and SOC state. Next, it uses a cosine function to generate an S-shaped transition curve to achieve smooth switching between the range extender and battery power. Furthermore, it improves system adaptability through parameter self-learning and optimization based on historical operating data. Considering the characteristics of commercial vehicles such as load variations and long-term operation, it designs a parameter calibration method that coordinates five modes: pure electric, range-extended charging, load following, power following, and fail-safe, as well as dynamic compensation of motor torque during mode switching to ensure continuous power output. The technical solution of this invention achieves intelligent operating mode management for range-extended commercial vehicles under complex operating conditions, ensuring smooth mode switching and optimal energy utilization while adapting to the characteristics of large load variations and complex operating conditions in commercial vehicles.

[0151] Example 2

[0152] Figure 2 This is a schematic diagram of a mode control device according to an embodiment of the present invention. This embodiment is applicable to the operation mode control of range-extended vehicles. The device can be implemented using software and / or hardware, and can be integrated into any device that provides mode control functionality, such as... Figure 2 As shown, the mode control device specifically includes: a first processing module 201, a second processing module 202, and a control module 203.

[0153] The first processing module 201 is used to acquire the operating parameters of the target vehicle and determine the current operating condition based on the operating parameters.

[0154] The second processing module 202 is used to obtain the battery status of the target vehicle and determine the target operating mode based on the current operating conditions and the battery status.

[0155] The control module 203 is used to control the target vehicle to switch to the target operating mode based on the S-curve transition strategy.

[0156] Optionally, the first processing module 201 is specifically used for:

[0157] The operating parameters are subjected to feature extraction to obtain an operating feature vector;

[0158] Based on the operating condition scoring function, the score corresponding to each type of operating condition is determined according to the operating feature vector;

[0159] The current operating condition is determined based on the score and confidence threshold corresponding to each type of operating condition.

[0160] Optionally, the second processing module 202 is specifically used for:

[0161] Based on the current operating conditions and the battery status, a preset decision matrix is ​​queried to determine the target operating mode.

[0162] Optionally, the device further includes:

[0163] The acquisition unit is used to acquire the switching timing strategy.

[0164] The generation unit is used to generate S-shaped curves.

[0165] Optionally, the generation unit is specifically used for:

[0166] Obtain the transition progress parameters, and construct an S-shaped transition factor function based on the transition progress parameters;

[0167] A power transition equation is constructed based on the S-shaped transition factor function; the power transition equation is: the actual power at the current moment is the product of the difference between the target power value and the initial power value, the sum of the target power value and the initial power value, and the S-shaped transition factor function.

[0168] The system acquires the power allocation strategy for mode switching, the power change rate limit, and the transition time; the power allocation strategy for mode switching includes: a pure electric mode switching to range-extended mode strategy and a range-extended mode switching to pure electric mode strategy.

[0169] Optionally, the current operating conditions include: urban delivery conditions, highway transportation conditions, mountain transportation conditions, heavy-load climbing conditions, and idling waiting conditions;

[0170] The target operating modes include: pure electric mode, range-extended charging mode, load following mode, power following mode, and fail-safe mode.

[0171] The above-mentioned products can execute the mode control method provided in any embodiment of the present invention, and have the corresponding functional modules and beneficial effects of the execution method.

[0172] Example 3

[0173] Figure 3A schematic diagram of an electronic device 30 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0174] like Figure 3 As shown, the electronic device 30 includes at least one processor 31 and a memory, such as a read-only memory (ROM) 32 or a random access memory (RAM) 33, communicatively connected to the at least one processor 31. The memory stores computer programs executable by the at least one processor. The processor 31 can perform various appropriate actions and processes based on the computer program stored in the ROM 32 or loaded from storage unit 38 into the RAM 33. The RAM 33 can also store various programs and data required for the operation of the electronic device 30. The processor 31, ROM 32, and RAM 33 are interconnected via a bus 34. An input / output (I / O) interface 35 is also connected to the bus 34.

[0175] Multiple components in electronic device 30 are connected to I / O interface 35, including: input unit 36, such as keyboard, mouse, etc.; output unit 37, such as various types of monitors, speakers, etc.; storage unit 38, such as disk, optical disk, etc.; and communication unit 39, such as network card, modem, wireless transceiver, etc. Communication unit 39 allows electronic device 30 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0176] Processor 31 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 31 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 31 performs the various methods and processes described above, such as mode control methods:

[0177] Obtain the operating parameters of the target vehicle, and determine the current operating condition based on the operating parameters;

[0178] Obtain the battery status of the target vehicle, and determine the target operating mode based on the current operating conditions and the battery status;

[0179] Based on the S-curve transition strategy, the target vehicle is controlled to switch to the target operating mode.

[0180] In some embodiments, the mode control method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 38. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 30 via ROM 32 and / or communication unit 39. When the computer program is loaded into RAM 33 and executed by processor 31, one or more steps of the mode control method described above may be performed. Alternatively, in other embodiments, processor 31 may be configured to execute the mode control method by any other suitable means (e.g., by means of firmware).

[0181] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0182] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0183] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0184] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0185] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0186] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0187] In one embodiment, the present invention further includes a computer program product, which includes a computer program that, when executed by a processor, implements the mode control method of any embodiment of the present invention.

[0188] In implementing the computer program product, computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0189] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0190] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A mode control method, characterized in that, include: Obtain the operating parameters of the target vehicle, and determine the current operating condition based on the operating parameters; Obtain the battery status of the target vehicle, and determine the target operating mode based on the current operating conditions and the battery status; Based on the S-curve transition strategy, the target vehicle is controlled to switch to the target operating mode.

2. The method according to claim 1, characterized in that, The current operating condition is determined based on the aforementioned operating parameters, including: The operating parameters are subjected to feature extraction to obtain an operating feature vector; Based on the operating condition scoring function, the score corresponding to each type of operating condition is determined according to the operating feature vector; The current operating condition is determined based on the score and confidence threshold corresponding to each type of operating condition.

3. The method according to claim 1, characterized in that, Determining the target operating mode based on the current operating conditions and the battery status includes: Based on the current operating conditions and the battery status, a preset decision matrix is ​​queried to determine the target operating mode.

4. The method according to claim 1, characterized in that, Before controlling the target vehicle to switch to the target operating mode based on the S-curve transition strategy, the following steps are also included: Obtain the switching timing strategy; Generate an S-shaped curve.

5. The method according to claim 4, characterized in that, Generating an S-shaped curve includes: Obtain the transition progress parameters, and construct an S-shaped transition factor function based on the transition progress parameters; A power transition equation is constructed based on the S-shaped transition factor function; the power transition equation is: the actual power at the current moment is the product of the difference between the target power value and the initial power value, the sum of the target power value and the initial power value, and the S-shaped transition factor function. The system acquires the power allocation strategy for mode switching, the power change rate limit, and the transition time; the power allocation strategy for mode switching includes: a pure electric mode switching to range-extended mode strategy and a range-extended mode switching to pure electric mode strategy.

6. The method according to claim 1, characterized in that, The current operating conditions include: urban delivery, highway transportation, mountain transportation, heavy-load uphill driving, and idling waiting conditions. The target operating modes include: pure electric mode, range-extended charging mode, load following mode, power following mode, and fail-safe mode.

7. A mode control device, characterized in that, include: The first processing module is used to acquire the operating parameters of the target vehicle and determine the current operating condition based on the operating parameters; The second processing module is used to obtain the battery status of the target vehicle and determine the target operating mode based on the current operating conditions and the battery status. The control module is used to control the target vehicle to switch to the target operating mode based on the S-curve transition strategy.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the mode control method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the mode control method according to any one of claims 1-6.

10. A computer program product comprising a computer program that, when executed by a processor, implements the mode control method according to any one of claims 1-6.

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