Energy management method for series-parallel hybrid electric vehicle based on separated ecms and soc-vehicle speed coupled power scheduling

Abstract

The application provides a kind of energy management method of hybrid electric vehicle based on separate ECMS and SOC-vehicle speed coupling electric quantity scheduling, comprising: obtaining vehicle operating parameters, vehicle operating parameters at least include battery state of charge, vehicle speed, current working mode, driver demand torque;According to the battery state of charge and the preset SOC hysteresis threshold value determines the electric quantity demand mode, according to the vehicle speed determines the vehicle speed sub-region, forms the joint state;Based on the joint state, the equivalent factor and the constraint parameter are determined by inquiring the pre-calibration mapping table;The optimal torque distribution parameter under the current working mode and the global optimal mode selection across multiple candidate working modes are calculated respectively using a separate optimization architecture;The optimal torque distribution parameter is output as a real-time driving command;When the global optimal mode selection is inconsistent with the current working mode, generate mode switching request and handle through state management mechanism.The application effectively improves the adaptability and system robustness of energy management.

Description

Technical Field

[0001] This invention relates to the field of hybrid vehicle energy management technology, specifically providing a hybrid vehicle energy management method based on a separate ECMS and SOC-vehicle speed coupled power dispatching. Background Technology

[0002] Equivalent Fuel Consumption Minimization (ECMS) is widely used in hybrid electric vehicle energy management due to its high computational efficiency and suitability for online real-time control. It optimizes instantaneous energy distribution by constructing a Hamiltonian function that incorporates the engine fuel consumption rate and the battery's equivalent fuel consumption rate, and then finding the operating points of each component that minimize this function within each control cycle.

[0003] Series-parallel hybrid electric vehicles (SPEVs) have multiple operating modes, including pure electric, series, and parallel operation, with different component states and constraints in each mode. Traditional ECMS typically calculates the globally optimal operating point across all modes and uses it for both torque output and mode decision-making. When the mode of the globally optimal operating point is inconsistent with the current actual mode, directly outputting the torque or speed command for the new mode will cause a mismatch between the command and the actual mode, resulting in sudden torque spikes and a deterioration in driving smoothness.

[0004] Furthermore, mode switching involves a multi-actuator coordination process, which can lead to response delays and switching failures. If the energy management strategy lacks mechanisms for intermediate request status, switching confirmation, failure rollback, and timeout handling, the control command may have already switched to the new mode before the switch is completed.

[0005] On the other hand, the setting of the equivalent factor in ECMS has a significant impact on the distribution of fuel and electricity. Existing strategies mostly only roughly divide the charging and discharging ranges based on SOC levels and configure different equivalent factors. However, charging efficiency and driving comfort are closely related to vehicle speed: at low speeds, high-power engine charging can easily cause noise, vibration, and frequent start-stop cycles; at medium to high speeds in steady state, the engine tends to operate in its high-efficiency zone, and appropriate charging is beneficial for subsequent low-speed electric drive. Relying solely on SOC for single-dimensional scheduling makes it difficult to balance low-speed NVH with medium to high-speed charging efficiency. Summary of the Invention

[0006] In order to overcome the above-mentioned defects, the present invention is proposed to provide a solution or at least a partial solution to the above-mentioned problems.

[0007] In a first aspect, the present invention provides a hybrid vehicle energy management method based on a separate ECMS and SOC-vehicle speed coupled energy dispatching, comprising the following steps: Obtain vehicle operating parameters, which include at least the battery state of charge, vehicle speed, current operating mode, and driver torque requirements. The SOC hysteresis power demand pattern is determined based on the battery state of charge and the SOC hysteresis threshold. The vehicle speed sub-region is determined based on the current vehicle speed. The SOC hysteresis power demand pattern and the vehicle speed sub-region are combined to form a joint state. Based at least on the joint state query precalibrated mapping table, determine the equivalent factor and the constraint parameters corresponding to the equivalent factor; Based on the equivalent factor, the constraint parameters, and the equivalent fuel consumption strategy, a separate optimization architecture is used to calculate the optimal torque distribution parameters under the current operating mode and the global optimal mode selection across multiple candidate operating modes. The optimal torque distribution parameters are output as a real-time drive command. When the globally optimal mode selection is inconsistent with the current working mode, a mode switching request is generated; The mode switching request is processed by a state management mechanism. The state management mechanism updates the working mode after receiving the switching completion signal from the mode switching execution unit, and reverts to the original working mode if the switching fails or times out. The global optimal mode selection is used only to generate the mode switching request, and is not directly used to output real-time driving commands.

[0008] Preferably, the split-optimized architecture includes: The current mode optimization unit is configured to calculate the power source operating parameters that match the current operating mode based on vehicle operating parameters, equivalent factors, and constraint parameters, under the constraints of the current operating mode, as the optimal torque distribution parameters for generating real-time drive commands; the global mode evaluation unit is configured to calculate the equivalent fuel consumption values ​​of pure electric mode, series mode, and parallel mode under the same driver torque demand conditions, under the same vehicle operating parameters, equivalent factors, and constraints, and select the mode with the smallest equivalent fuel consumption value as the global optimal mode selection.

[0009] The output of the current mode optimization unit is used for real-time drive control, and the output of the global mode evaluation unit is used for mode switching decisions.

[0010] Preferably, the current mode optimization unit calculates the optimal torque distribution parameters, specifically including: When the current working mode is pure electric mode, under the constraints of motor output capacity and battery discharge power, the drive motor torque is calculated based on the current vehicle speed and the driver's required torque to make the electric drive system most efficient or the equivalent energy consumption least, and the engine speed and engine torque are both zero. When the current operating mode is series mode, the engine speed, engine torque, generator torque and drive motor torque are determined based on the driver's power demand, the engine's efficient operating range and generator constraints, so as to minimize the equivalent fuel consumption value in series mode. When the current operating mode is parallel mode, the distribution of engine torque and motor torque is determined based on the current vehicle speed, driver's required torque, battery state of charge, equivalent factor, and constraints of the engine, motor, and battery, so as to minimize the equivalent fuel consumption value in parallel mode.

[0011] Preferably, the global mode evaluation unit calculates the equivalent fuel consumption value for each operating mode, specifically including: For each candidate operating mode in pure electric mode, series mode and parallel mode, the corresponding equivalent fuel consumption value is calculated under a unified equivalent fuel consumption function framework. The equivalent fuel consumption function includes an engine fuel consumption term, a battery energy exchange equivalent term, and a penalty term. The battery energy exchange equivalent term is determined based on battery power and equivalent factor. The battery power is used to characterize the battery charge and discharge state, and the battery discharge state corresponds to positive power, while the battery charging state corresponds to negative power. Within the framework of the unified equivalent fuel consumption function, the pure electric mode, series mode, and parallel mode are solved under their respective constraints, and the working mode with the minimum equivalent fuel consumption value is selected as the global optimal mode.

[0012] Preferably, the state management mechanism includes: Request status: Entered after generating a mode switching request, while maintaining the current working mode unchanged, and sending a switching command to the mode switching execution unit; Confirmation status: Wait for the switching status signal from the receiving mode switching execution unit, and set the preset timeout threshold; Completion status: When a switching completion signal is received within the preset timeout threshold, the current working mode is updated to the target mode, and the intermediate request status is cleared; Rollback state: If a switching completion signal is not received or a switching failure signal is received after the preset timeout threshold is exceeded, the mode switching request is canceled and the original working mode is maintained; During the state transition process, the optimal torque distribution parameters are always generated based on the current operating mode.

[0013] Preferably, the power demand mode includes multiple SOC hysteresis modes, each SOC hysteresis mode having an entry threshold and an exit threshold, and the entry threshold and the exit threshold are different; at least one SOC hysteresis mode is provided with multiple vehicle speed sub-regions; The vehicle speed sub-region includes a low-speed sub-region, a medium-speed sub-region, and a high-speed sub-region; Different charging tendency, discharging tendency, or battery maintenance tendency correspond to different vehicle speed sub-regions, and the charging tendency, discharging tendency, or battery maintenance tendency is achieved by at least one of the following: equivalent factor, active power generation permission, active power generation upper limit, engine start-stop penalty parameter, and NVH penalty parameter.

[0014] Secondly, the present invention provides a hybrid vehicle energy management system based on a separate ECMS and SOC-vehicle speed coupled energy dispatching, comprising: The data acquisition module is used to acquire vehicle operating parameters, which include at least the battery state of charge, vehicle speed, current operating mode, and driver torque requirements. The equivalent factor and constraint parameter determination module is used to determine the SOC hysteresis power demand pattern based on the battery state of charge and the SOC hysteresis threshold, determine the vehicle speed sub-region based on the vehicle speed, and determine the equivalent factor and the constraint parameters corresponding to the equivalent factor based at least on the joint state formed by the SOC hysteresis power demand pattern and the vehicle speed sub-region. The separate optimization calculation module is configured to calculate the optimal torque distribution parameters under the current working mode and the global optimal mode selection across multiple candidate working modes based on the equivalent factor, the constraint parameters and the equivalent fuel consumption strategy. The command output module is used to output the optimal torque distribution parameters as a real-time drive command to the vehicle power system. The switching request generation module is used to generate a mode switching request when the globally optimal mode selection is inconsistent with the current working mode; The status management module is configured to process the mode switching request, update the working mode after receiving the switching completion signal from the mode switching execution unit, and revert to the original working mode if the switching fails. The global optimal mode selection is used only to generate the mode switching request, and is not directly used to output real-time driving commands.

[0015] Thirdly, the present invention provides a vehicle including the aforementioned hybrid vehicle energy management system based on a separate ECMS and SOC-vehicle speed coupled power dispatching.

[0016] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method.

[0017] The beneficial effects of this invention are as follows: First, this invention decouples the current execution control from the mode switching decision through a separate ECMS solution and a dual-output mechanism. The optimal operating point within the current mode is used for torque or speed output, while the globally optimal operating point is only used for generating mode switching requests, thereby reducing the risk of sudden torque changes near the mode switching boundary.

[0018] Second, the present invention improves the reliability and robustness of mode switching by using intermediate request status, successful switching confirmation, failure rollback and timeout handling mechanisms to keep the upper-layer energy management strategy consistent with the actual state of the lower-layer actuator.

[0019] Third, this invention uses the SOC hysteresis mode and the vehicle speed sub-region coupling scheduling equivalent factor to limit unreasonable high-power active charging in low-speed, low-SOC scenarios, and allows the engine to charge in the high-efficiency zone in medium- and high-speed scenarios, thereby taking into account fuel economy, low-speed NVH and subsequent electric drive requirements.

[0020] Fourth, this invention inputs the power dispatch intention into the ECMS through equivalent factors, active generation permits, power limits, and penalty terms, rather than directly and rigidly specifying the operating point of the engine or motor. Therefore, it retains the online optimization capability of the ECMS and reduces the oscillations caused by hard rule switching. Attached Figure Description

[0021] The disclosure of this invention will become more readily understood with reference to the accompanying drawings. It will be readily understood by those skilled in the art that these drawings are for illustrative purposes only and are not intended to limit the scope of protection of this invention. Furthermore, similar numbers in the drawings are used to denote similar components, wherein: Figure 1 This is a schematic diagram of the main steps of a hybrid vehicle energy management method based on a split ECMS and SOC-vehicle speed coupled power scheduling according to an embodiment of the present invention.

[0022] Figure 2 This is a schematic diagram of a split ECMS solver and dual-output logic according to an embodiment of the present invention.

[0023] Figure 3 This is a schematic diagram of an intermediate request state machine for mode switching according to an embodiment of the present invention.

[0024] Figure 4 This is a schematic diagram of power demand scheduling coupled with SOC hysteresis mode and vehicle speed sub-region according to an embodiment of the present invention.

[0025] Figure 5 This is a schematic diagram of the equivalent factor mapping and constraint scheduling structure according to an embodiment of the present invention. Detailed Implementation

[0026] Some embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0027] like Figure 1 As shown, this invention provides an energy management method for parallel-connected hybrid vehicles based on a separate ECMS and SOC-vehicle speed coupled energy dispatching. This method can be executed in each control cycle to achieve real-time energy distribution optimization for the vehicle. Please refer to [link to relevant documentation]. Figure 1 The method includes the following steps: Step S1: Obtain vehicle operating parameters; In this embodiment, the vehicle operating parameters include at least the battery state of charge (SOC), vehicle speed, current operating mode, and driver-required torque. Preferably, the vehicle operating parameters may also include engine speed, motor speed, battery charge / discharge power limits, engine status, motor status, and necessary temperature signals.

[0028] Of course, vehicle operating parameters are not limited to those listed above, and may also include other parameters that affect energy management strategies, such as battery temperature, ambient temperature, and air conditioning power. Those skilled in the art can flexibly adjust and set these parameters according to actual control needs.

[0029] In one embodiment, after obtaining the vehicle operating parameters, the method further includes determining the power demand pattern based on the State of Charge (SOC) and a preset SOC hysteresis threshold, and determining the vehicle speed sub-region based on the vehicle speed within at least a portion of the power demand patterns, thereby obtaining the joint state of the power demand pattern and the vehicle speed sub-region.

[0030] Furthermore, when the State of Charge (SOC) changes from high to low or from low to high, the power demand mode does not switch at the same threshold. Instead, it employs a hysteresis mechanism with different entry and exit thresholds. For example, when the SOC drops below the first entry threshold, it enters a safety power-saving mode, and only exits this mode when the SOC rises above the first exit threshold.

[0031] The power demand pattern includes multiple SOC hysteresis modes, each with an entry threshold and an exit threshold, and the entry and exit thresholds are different. By setting different entry and exit thresholds, hysteresis characteristics are formed, which can prevent frequent changes in the power demand pattern when the SOC is near the threshold.

[0032] The power demand mode includes 7 modes: Mode 1 is the low SOC safety power preservation mode, which prioritizes the vehicle's basic functions when the SOC is close to the safety lower limit; Mode 2 is the low SOC replenishment mode, which restores power when the SOC is low; Mode 3 is the medium-low SOC speed-coupled replenishment mode, which balances replenishment and driving comfort when the SOC is medium-low; Mode 4 is the medium SOC speed-coupled maintenance mode, which maintains the current power level when the SOC is in a moderate range; Mode 5 is the medium-high SOC discharge mode, which slowly releases power when the SOC is high; Mode 6 is the high SOC discharge mode, which increases the tendency to use power when the SOC is high; and Mode 7 is the excessively high SOC rapid discharge or prohibited active charging mode, which reserves space for regenerative braking when the SOC is too high.

[0033] For example, the threshold values ​​for each SOC mode can be set as follows: Mode 1 (Safety Power Preservation) has an entry threshold of SOC < 18% and an exit threshold of SOC > 23%; Mode 2 (Low SOC Charging) has an entry threshold of SOC < 24% and an exit threshold of SOC > 28%; Mode 3 (Medium-Low SOC Vehicle Speed ​​Coupling Charging) has an entry threshold of SOC < 35% and an exit threshold of SOC > 40%; Mode 4 (Medium SOC Vehicle Speed ​​Coupling Maintenance) has an entry threshold of SOC < 50% and an exit threshold of SOC > 55%; Mode 5 (Medium-High SOC Discharge) has an entry threshold of SOC < 70% and an exit threshold of SOC > 75%; Mode 6 (High SOC Discharge) has an entry threshold of SOC < 85% and an exit threshold of SOC > 88%; and Mode 7 (Excessively High SOC Fast Discharge / Charging Prohibition) has an entry threshold of SOC > 90% and an exit threshold of SOC < 87%. Of course, the specific values ​​of the entry and exit thresholds for each of the above modes are merely illustrative examples. Those skilled in the art can flexibly adjust and set them according to the battery characteristics, motor efficiency, and overall vehicle energy consumption targets of a specific vehicle model.

[0034] The vehicle speed sub-region includes a low-speed sub-region, a medium-speed sub-region, and a high-speed sub-region.

[0035] For example, the low-speed sub-region can be defined as a vehicle speed < 30 km / h, the medium-speed sub-region as 30 km / h ≤ vehicle speed < 60 km / h, and the high-speed sub-region as a vehicle speed ≥ 60 km / h. Of course, the specific values ​​of the above vehicle speed thresholds are merely illustrative examples, and those skilled in the art can flexibly adjust and set them according to the powertrain characteristics and NVH performance of a specific vehicle model. Multiple vehicle speed sub-regions are set within at least one SOC hysteresis mode, and the SOC hysteresis energy demand mode is combined with the vehicle speed sub-regions to form a joint state. This joint state is used not only to determine the equivalence factor but also to determine the constraint parameters corresponding to the equivalence factor, thereby achieving different charging tendencies, discharging tendencies, or energy maintenance tendencies within different vehicle speed sub-regions.

[0036] Specifically, in the low-SOC vehicle speed coupled charging mode (Mode 3) and when the vehicle speed is in the low-speed sub-region, the strategy reduces the equivalence factor or limits the active power generation of the engine to avoid NVH deterioration caused by low-speed high-power charging. For example, the equivalence factor of the low-speed sub-region can be set to 0.8 to 1.2 in the equivalence factor mapping table, while the upper limit of the low-speed active power generation is limited to 5kW to 10kW.

[0037] When the State of Charge (SOC) is in the low-to-medium SOC vehicle speed coupled charging mode and the vehicle speed is in the medium-speed or high-speed sub-region, the strategy increases the equivalence factor or allows the engine to charge in the high-efficiency operating range. For example, the equivalence factor for the medium-speed or high-speed sub-region can be set to 1.5 to 2.5, allowing the engine to charge at a power of 15kW to 30kW on the optimal fuel economy operating line.

[0038] For the medium SOC vehicle speed coupling maintenance mode (mode 4), the low-speed sub-region can be biased towards pure electric or slight discharge, the medium-speed sub-region can be biased towards battery maintenance or slow charging, and the high-speed sub-region can allow moderate battery replenishment when the engine is running at high efficiency.

[0039] For medium-high SOC modes (Mode 5) and high SOC modes (Mode 6), the strategy can favor discharge and limit active charging to reserve space for regenerative braking. For excessively high SOC rapid discharge or active charging prohibited modes (Mode 7), the strategy prohibits active charging and prioritizes the use of electric power.

[0040] Table 1 illustrates an exemplary coupling relationship between SOC hysteresis mode and vehicle speed sub-region. This table is for illustrative purposes only and does not limit specific thresholds or calibration values.

[0041] Table 1

[0042] In one embodiment, such as Figure 5 As shown, the specific value of the equivalent factor is obtained by querying a pre-calibrated equivalent factor mapping table. This mapping table uses the joint state of driving scenario, driving style, and power demand mode with vehicle speed sub-region as a joint index. The equivalent factor can not only serve as the weight of the battery equivalent fuel consumption term in the Hamiltonian function, but also correspond to the configuration of upper and lower limits, rate of change limits, active power generation permission status, low-speed active power generation upper limit, engine start-stop penalty, and NVH penalty parameters of the equivalent factor. Thus, the power scheduling intention is reflected through the ECMS objective function and constraints, rather than directly specifying the operating point of the engine or motor through hard switching.

[0043] Driving scenarios can include urban congestion, smooth urban traffic, suburban areas, highways, mountainous areas, or slopes. For example, urban congestion scenarios can be identified by the braking frequency per unit time (e.g., more than 5 braking times per minute) and average vehicle speed (e.g., less than 15 km / h); highway scenarios can be identified by average vehicle speed (e.g., more than 80 km / h); and mountainous or sloped scenarios can be identified by the rate of change of longitudinal acceleration or GPS altitude information.

[0044] Of course, the methods for recognizing driving scenarios are not limited to those listed above. Those skilled in the art can also use alternative methods such as navigation map information, camera visual recognition, or V2X communication for scenario recognition.

[0045] Driving styles can include Eco, Balanced, and Sport. For example, the driving style can be determined by the driver manually selecting it (such as by selecting Eco, Standard, or Sport mode via a driving mode switch).

[0046] In an alternative approach, driving style can also be automatically identified by the rate of change of accelerator pedal opening: when the rate of change of accelerator pedal opening is greater than a preset threshold (e.g., 50% / s), it is determined to be a sporty style; when the rate of change of accelerator pedal opening is less than a preset threshold (e.g., 20% / s), it is determined to be an economy style; and when it is in between, it is a balanced style.

[0047] Of course, the methods for identifying driving styles are not limited to those listed above. Those skilled in the art can also use alternative methods such as machine learning algorithms or fuzzy logic to identify driving styles.

[0048] In one embodiment, the equivalent factor mapping table not only outputs the equivalent factor value, but also simultaneously outputs at least one of the following constraint parameters: equivalent factor upper limit, equivalent factor lower limit, equivalent factor rate of change limit, active generation permit flag, low-speed generation power upper limit, engine start-stop penalty coefficient, and NVH penalty coefficient. Through this method, the power dispatching intent is reflected by both the ECMS objective function and constraints, rather than directly specifying the operating point of the engine or motor through hard switching. This preserves the online optimization capabilities of the ECMS and reduces oscillations caused by rule-based hard switching.

[0049] In one implementation, the low-speed NVH penalty is determined jointly based on vehicle speed and SOC mode. When the vehicle speed is below a preset low-speed threshold (e.g., 30 km / h), an additional penalty is applied to candidate operating points where the engine's active power generation exceeds a preset power limit. This preset power limit can be moderately increased as the SOC decreases to balance safety and power supply requirements. For example, in a low SOC safety power supply mode, the upper limit of low-speed power generation can be relaxed to 15 kW; in a medium-low SOC vehicle speed coupled power supply mode, the upper limit of low-speed power generation can be limited to 8 kW. Of course, the above power limit values ​​are only illustrative examples, and those skilled in the art can flexibly adjust and set them according to the NVH performance and engine characteristics of a specific vehicle model.

[0050] In an alternative approach, determining whether a mode switch is necessary can be achieved by: calculating the difference between the equivalent fuel consumption value corresponding to the globally optimal mode selection and the equivalent fuel consumption value of the optimal operating point within the current mode; determining whether this difference is greater than or equal to a preset switching threshold; if the difference is greater than or equal to the preset switching threshold, it indicates that switching to the globally optimal mode can bring significant fuel economy benefits, and a mode switch request is generated; if the difference is less than the preset switching threshold, it indicates that the switching benefits are insufficient to compensate for the NVH and driving smoothness costs brought by the mode switch, and a mode switch request is not generated. The preset switching threshold can be set from 0.5kW to 2kW (in terms of equivalent fuel power), preferably 1kW. Of course, the preset switching threshold is not limited to the values ​​listed above, and those skilled in the art can flexibly adjust and set it according to the calibration results of specific vehicle models, as long as frequent mode changes caused by switching with minimal benefits are avoided.

[0051] Regardless of the determination method used, as long as a mode switching request can be generated when the globally optimal mode selection is inconsistent with the current working mode, and the request can be handled through the state management mechanism, it is acceptable.

[0052] Step S2: Based on the equivalent fuel consumption strategy, a separate optimization architecture is used to calculate the optimal torque distribution parameters under the current working mode and the global optimal mode selection across multiple working modes. Specifically, the split optimization architecture includes a current mode optimization unit and a global mode evaluation unit. The current mode optimization unit is configured to calculate the optimal torque distribution parameters for engine speed, engine torque, and electric motor torque that meet the driver's required torque under the constraints of the current operating mode. The global mode evaluation unit is configured to calculate the equivalent fuel consumption values ​​for pure electric mode, series mode, and parallel mode under the same driver's required torque conditions, and select the mode with the minimum equivalent fuel consumption value as the globally optimal mode.

[0053] like Figure 2As shown, the ECMS solver calculates the Hamiltonian function within the pure electric, series, and parallel candidate point sets, and obtains... , and Simultaneously, all candidate points are merged to form a global candidate set, and the global optimum is extracted. and its associated model .

[0054] In one embodiment, the equivalent fuel consumption value is calculated based on the Hamiltonian function, which can be expressed as: in, Engine fuel consumption rate. As the current equivalent factor, For battery power, Because it is a low-calorific-value fuel, This is the sum of penalty items. Penalty items may include mode switching time penalty items, low-speed NVH penalty items, engine start-stop penalty items, operating point jump penalty items, battery power boundary penalty items, and thermal management constraint penalty items, etc.

[0055] In one embodiment, before performing calculations based on the equivalent fuel consumption strategy, a step of determining an equivalence factor is included. The equivalence factor is determined as follows: the current energy demand mode is determined based on the battery state of charge; the vehicle speed sub-region is determined based on the current vehicle speed; and the equivalence factor is obtained by querying a pre-calibrated equivalence factor mapping table using the driving scenario, driving style, and the joint state of the energy demand mode and the vehicle speed sub-region as a joint index. The energy demand mode, vehicle speed sub-region, driving scenario, and driving style are described in detail below.

[0056] The current mode optimization unit calculates the optimal torque distribution parameters in the following specific way: When the current operating mode is pure electric, the engine is not running, and traction power is provided by the battery and drive motor. Based on the current vehicle speed and the driver's required torque, the optimal torque distribution parameters that maximize motor efficiency are calculated, with both engine speed and engine torque at zero. If the driver's required torque exceeds the capabilities of pure electric mode, the candidate operating point in that mode can be marked as infeasible.

[0057] When the current operating mode is series mode, the engine and wheels are mechanically decoupled. The engine drives the generator to produce electricity, and the drive motor provides wheel-end torque. Based on the current vehicle speed and the driver's required torque, the engine speed that positions the engine at the optimal fuel consumption curve, and the generator torque that satisfies battery power balance, are calculated. Specifically, several candidate operating points can be discretized along the engine's optimal fuel economy operating line according to power steps (e.g., 1kW or 2kW). The generator power and battery power are calculated based on power balance, and it is checked whether the battery charge and discharge power boundary constraints are met. Finally, the operating point that optimizes system efficiency is selected.

[0058] When the current operating mode is parallel, the engine and wheels are mechanically coupled. Based on the current vehicle speed, driver-demanded torque, and battery state of charge, the optimal engine torque and motor torque distribution ratio that maximizes the overall system efficiency is calculated. Specifically, the engine speed is determined by the current vehicle speed and transmission ratio, the engine torque is discrete within the allowable operating range at the current speed, and the motor torque is determined by the difference between the driver-demanded torque and the engine-contributed torque. The constraints of the engine, motor, battery, and transmission system are examined for each candidate point, and the allocation scheme that maximizes the overall system efficiency is selected.

[0059] In one embodiment, the global mode evaluation unit calculates the equivalent fuel consumption value for each operating mode, specifically including: In pure electric mode, the equivalent fuel consumption rate is calculated by multiplying the battery discharge power by an equivalent factor. In this mode, the engine fuel consumption rate is zero, and the equivalent fuel consumption occurs when the battery power is positive (discharging).

[0060] For series mode, the equivalent fuel consumption rate is calculated by adding the actual fuel consumption rate of the engine to the net power of the battery and multiplying by the equivalent factor. A positive net power of the battery indicates that the battery is discharging, while a negative net power indicates that the battery is charging. During charging, the equivalent fuel consumption is negative (i.e., fuel savings calculated from recovered energy).

[0061] For parallel operation, the equivalent fuel consumption rate is calculated by adding the actual fuel consumption rate of the engine to the auxiliary power of the electric motor and multiplying by an equivalent factor. A positive auxiliary power value indicates that the electric motor consumes electrical energy to drive the engine, while a negative value indicates that the electric motor is in a generator state, charging the battery.

[0062] A mode-switching penalty is added to each equivalent fuel consumption value. The penalty is dynamically adjusted based on the time interval since the last mode switch; the shorter the time interval, the greater the penalty weight. Specifically, when the time interval since the last mode switch is less than 1.5 seconds, the penalty weight can be set to 0.3 to 0.5; when the time interval is greater than or equal to 1.5 seconds, the penalty weight can be set to 0.05 to 0.1. Of course, the 1.5-second time threshold and the weight ranges of 0.3-0.5 and 0.05-0.1 mentioned above are merely illustrative examples. Those skilled in the art can flexibly adjust and set these values ​​according to the specific vehicle's switching response characteristics and smoothness requirements, as long as the effect of suppressing frequent mode switching is achieved.

[0063] Step S3: Output the optimal torque distribution parameters as a real-time drive command; In the output stage, this invention does not directly output the torque or speed command for the globally optimal operating point. Specifically, it outputs the optimal torque distribution parameters for the current operating mode as the real-time drive command. When the globally optimal mode selection differs from the current operating mode, a mode switching request is generated.

[0064] like In pure electric mode, the torque output adopts... ;like In series mode, torque and speed output are achieved using... ;like In parallel mode, the torque output adopts... .regardless What is the corresponding globally optimal mode before the mode switch is complete? None of them directly participate in the output of torque or speed commands.

[0065] when and If the switching direction is different and allowed, the dual-output unit generates a corresponding mode switching request; otherwise, no switching request is generated. This logic ensures that the currently executed command is always consistent with the current actual mode.

[0066] The cross-mode global optimal operating point is only used to determine whether a mode switch is needed.

[0067] Through the aforementioned dual-output mechanism, the vehicle always uses the optimal operating point within the current actual mode as the control command before the mode switch is completed, thus avoiding command step jumps and physical mode mismatches caused by sudden changes in the global optimal mode.

[0068] Step S4: When the globally optimal mode selection is inconsistent with the current operating mode, the energy management controller does not immediately update the actual operating mode, but instead generates an intermediate request state. Intermediate request states may include requests to switch from pure electric mode to series mode, requests to switch from series mode to parallel mode, requests to switch from parallel mode to series mode, and requests to switch from series mode to pure electric mode.

[0069] Upon receiving an intermediate request status, the mode switching execution unit performs the corresponding engine start, speed synchronization, clutch actuation, or generator adjustment process. Only when the switching execution unit sends a successful switching signal will the energy management controller update the current operating mode to the new mode and clear the intermediate request status. If the switching fails or times out, the energy management controller maintains the current operating mode and clears the intermediate request status or enters a no-retry time window.

[0070] like Figure 3 As shown, the energy management controller can define intermediate request states such as EV2SER, SER2PAR, PAR2SER, and SER2EV. Taking EV2SER as an example, when the vehicle's current actual mode is pure electric mode, and the globally optimal mode is series mode, and the lower-level controller allows switching from pure electric mode to series mode, the energy management controller outputs the EV2SER intermediate request state.

[0071] Upon receiving the EV2SER request, the mode switching execution unit performs engine start, speed establishment, generator coordination, and necessary coupling actions. If the switch is complete, a success signal is sent, and the upper-level controller will... Update to serial mode; if feedback fails or the preset timeout period is exceeded without success, the upper-level controller maintains [the status quo]. In pure electric mode, EV2SER requests are cleared, and duplicate requests can be prohibited for a certain period of time.

[0072] Similarly, switching between serial and parallel modes is also done through corresponding intermediate request statuses, success confirmations, and failure rollbacks.

[0073] Step S5: During the mode switching process, the present invention handles the mode switching request through a state management mechanism.

[0074] In one embodiment, the state management mechanism includes request state, confirmation state, completion state, and rollback state. The following describes... Figure 3 Each state is described in detail.

[0075] Request State: This state is entered after generating a mode switching request, while maintaining the current operating mode and sending a switching command to the mode switching execution unit. In the request state, the optimal torque distribution parameters continue to be generated based on the current operating mode, rather than based on the target mode.

[0076] Confirmation status: After entering the confirmation status, start the timer and wait for the switching status signal fed back by the mode switching execution unit.

[0077] Completion Status: When a switch completion signal is received within the preset timeout threshold, the system enters the completion status. In the completion status, the current working mode is updated to the target mode, and the intermediate request status is cleared.

[0078] Rollback State: When a switchover completion signal is not received within a preset timeout threshold, or a switchover failure signal is received, the system enters the rollback state. In the rollback state, the mode switch request is cancelled and the original operating mode remains unchanged, while the intermediate request state is cleared. Preferably, after entering the rollback state, a retry prohibition timer (e.g., set to 3 to 10 seconds) can be started. Before this timer reaches zero, a switchover request to the same target mode is prohibited again to avoid frequent retries that could cause system instability.

[0079] Throughout the entire transition process from the request state, confirmation state, completion state, and rollback state, the optimal torque distribution parameters are always generated based on the current operating mode. That is, even if a mode switching request has been generated before the mode switching execution unit sends back the switching completion signal, the control command is still output based on the optimal torque distribution parameters of the original operating mode, thereby avoiding command mismatch and torque mutation caused by mode switching delay.

[0080] In one embodiment, to prevent system oscillation caused by frequent mode switching, the present invention may also set a forced hold time after a mode switch is completed. During the preset hold time after a mode switch is completed, the generation of mode switch requests to switch back to the previous working mode is prohibited.

[0081] Alternatively, an alternative approach is to impose an additional penalty on the return mode immediately after the switch within the Hamiltonian function. This penalty decays over time until it is completely eliminated. Whether a mandatory hold time or an additional penalty is used, the key is to prevent frequent mode switching.

[0082] The following describes the implementation of this invention using an urban expressway driving scenario as an example. The vehicle is traveling at 75 km / h, with a State of Charge (SOC) in the low to medium range (e.g., SOC = 32%), and the current operating mode is pure electric mode. The power demand mode determination unit determines that the SOC is in the low to medium SOC vehicle speed coupled charging mode (mode 3), and the vehicle speed is in the high-speed sub-region. The equivalent factor determination unit obtains the equivalent factor by querying the mapping table based on the driving scenario (urban expressway), driving style (balanced), and joint state (mode 3 - high-speed sub-region), for example, s(t) = 1.8. After ECMS solution, the optimal point in pure electric mode can satisfy the current torque output, but the global optimal point across modes belongs to the parallel mode (because in the parallel mode, the engine is in the high-efficiency zone and can charge simultaneously).

[0083] Since the current operating mode is pure electric mode, the dual-output unit still outputs the motor torque command (e.g., 150 Nm) at the optimal operating point within pure electric mode, while simultaneously generating an intermediate request state EV2SER for transitioning from pure electric mode to series mode. Upon receiving the EV2SER request, the mode switching execution unit performs engine start, speed establishment, and generator coordination actions. If the switch is successful, a success signal is fed back, and the current operating mode is updated to series mode. In the next control cycle, if the globally optimal mode is still parallel mode, an intermediate request state SER2PAR for transitioning from series to parallel is generated. Throughout this process, the torque command is always taken from the optimal point within the current operating mode, reducing the torque step caused by mode switching. If a switching failure or timeout occurs during any switching process, the system reverts to the operating mode before the switch, and the vehicle continues to operate in the original mode.

[0084] The following example, using a low-speed driving scenario, illustrates the power dispatching effect of this invention. The vehicle is traveling at a low speed of 25 km / h, with a State of Charge (SOC) in the low-to-medium range (e.g., SOC = 34%), in a low-to-medium SOC speed-coupled power replenishment mode (Mode 3), and the vehicle speed is within a low-speed sub-region. Traditional strategies based solely on SOC may request high-power engine power replenishment due to a low SOC. In this invention, the low-speed sub-region restricts the equivalent factor (e.g., s(t) = 0.9), and the low-speed NVH penalty term imposes additional penalties on candidate points for high-power engine power generation, limiting the upper limit of low-speed active power generation to 8 kW. Based on these constraints, the ECMS performs optimization, allowing selection of feasible operating points such as pure electric drive, low-power power generation, or delayed power replenishment, thus avoiding NVH degradation caused by high-power low-speed power replenishment.

[0085] If the State of Charge (SOC) is further reduced to a low SOC charging mode (e.g., SOC drops to 22%), the safety priority is increased, and the strategy allows the engine to intervene in charging. However, the charging intensity can still be controlled by the low-speed power generation limit (e.g., 12kW), minimum start-up time, and NVH penalty terms to avoid frequent start-stop and excessive noise. When the vehicle speed increases to the medium-speed or high-speed sub-region, the equivalence factor increases (e.g., s(t)=2.0), and the active power generation limit is relaxed, allowing the engine to charge at a power of 20kW to 30kW in the high-efficiency operating range, providing energy reserves for subsequent low-speed electric drive.

[0086] In summary, this invention decouples the current execution control from the mode switching decision through a separate ECMS solution and a dual-output mechanism; improves the reliability and robustness of mode switching through intermediate request states, successful switching confirmation, failure rollback, and timeout handling mechanisms; and balances fuel economy, low-speed NVH, and subsequent electric drive requirements through SOC hysteresis mode and vehicle speed sub-region coupled scheduling equivalence factors. Those skilled in the art will understand that the specific values ​​in the above embodiments (such as SOC threshold, vehicle speed threshold, equivalence factor range, timeout threshold, power limit value, etc.) are illustrative and not limiting to the invention. In practical applications, the above parameters can be calibrated and optimized according to the powertrain parameters, battery characteristics, NVH performance targets, and fuel economy requirements of specific vehicle models, as long as they do not depart from the concept of this invention.

[0087] Example 2 This invention provides a hybrid vehicle energy management system based on a separate ECMS and SOC-vehicle speed coupled energy dispatching, comprising: The data acquisition module is used to acquire vehicle operating parameters, which include at least the battery state of charge, vehicle speed, current operating mode, and driver torque requirements. The equivalent factor and constraint parameter determination module is used to determine the SOC hysteresis power demand pattern based on the battery state of charge and the SOC hysteresis threshold, determine the vehicle speed sub-region based on the vehicle speed, and determine the equivalent factor and the constraint parameters corresponding to the equivalent factor based at least on the joint state formed by the SOC hysteresis power demand pattern and the vehicle speed sub-region. The separate optimization calculation module is configured to calculate the optimal torque distribution parameters under the current working mode and the global optimal mode selection across multiple candidate working modes based on the equivalent factor, the constraint parameters and the equivalent fuel consumption strategy. The command output module is used to output the optimal torque distribution parameters as a real-time drive command to the vehicle power system. The switching request generation module is used to generate a mode switching request when the globally optimal mode selection is inconsistent with the current working mode; The status management module is configured to process the mode switching request, update the working mode after receiving the switching completion signal from the mode switching execution unit, and revert to the original working mode if the switching fails. The global optimal mode selection is used only to generate the mode switching request, and is not directly used to output real-time driving commands.

[0088] Example 3 An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the aforementioned energy management method for a series-parallel hybrid vehicle based on a split ECMS and SOC-vehicle speed coupled power scheduling.

[0089] Example 4 The present invention also provides a computer-readable storage medium. In one embodiment of the present invention, the computer-readable storage medium can be configured to store a program that executes the hybrid electric vehicle energy management method based on separate ECMS and SOC-vehicle speed coupled power scheduling according to the above-described method embodiments. This program can be loaded and run by a processor to implement the above-described hybrid electric vehicle energy management method based on separate ECMS and SOC-vehicle speed coupled power scheduling. For ease of explanation, only the parts related to the embodiments of the present invention are shown; for specific technical details not disclosed, please refer to the method section of the embodiments of the present invention. The computer-readable storage medium can be a storage device comprising various electronic devices. Optionally, in the embodiments of the present invention, the computer-readable storage medium is a non-transitory computer-readable storage medium.

[0090] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make the same modifications or substitutions to the original technical features, and the technical solutions after these modifications or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A hybrid electric vehicle energy management method based on separate ECMS and SOC-vehicle speed coupled power scheduling, characterized in that, Includes the following steps: Obtain vehicle operating parameters, which include at least the battery state of charge, vehicle speed, current operating mode, and driver torque requirements. The SOC hysteresis power demand pattern is determined based on the battery state of charge and the SOC hysteresis threshold. The vehicle speed sub-region is determined based on the current vehicle speed. The SOC hysteresis power demand pattern and the vehicle speed sub-region are combined to form a joint state. Based at least on the joint state query precalibrated mapping table, determine the equivalent factor and the constraint parameters corresponding to the equivalent factor; Based on the equivalent factor, the constraint parameters, and the equivalent fuel consumption strategy, a separate optimization architecture is used to calculate the optimal torque distribution parameters under the current operating mode and the global optimal mode selection across multiple candidate operating modes. The optimal torque distribution parameters are output as a real-time drive command. When the globally optimal mode selection is inconsistent with the current working mode, a mode switching request is generated; The mode switching request is processed by a state management mechanism. The state management mechanism updates the working mode after receiving the switching completion signal from the mode switching execution unit, and reverts to the original working mode when the switching fails. The global optimal mode selection is used only to generate the mode switching request, and is not directly used to output real-time driving commands.

2. The method of claim 1, wherein, The split-optimization architecture includes: The current mode optimization unit is configured to calculate the power source operating parameters that match the current operating mode based on vehicle operating parameters and equivalent factors under the constraints corresponding to the current operating mode, and use them as the optimal torque distribution parameters for generating real-time drive commands. The global mode evaluation unit is configured to calculate the equivalent fuel consumption values ​​of multiple candidate working modes under the same vehicle operating parameters, equivalent factors and constraints, and select the candidate working mode with the smallest equivalent fuel consumption value as the global optimal mode selection. The output of the current mode optimization unit is used for real-time drive control, and the output of the global mode evaluation unit is used for mode switching decisions.

3. The method of claim 2, wherein, The current mode optimization unit calculates the optimal torque distribution parameters, specifically including: When the current working mode is pure electric mode, under the constraints of motor output capacity and battery discharge power, the drive motor torque is calculated based on the current vehicle speed and the driver's required torque to make the electric drive system most efficient or the equivalent energy consumption least, and the engine speed and engine torque are both zero. When the current operating mode is series mode, the engine speed, engine torque, generator torque and drive motor torque are determined based on the driver's power demand, the engine's efficient operating range and generator constraints, so as to minimize the equivalent fuel consumption value in series mode. When the current operating mode is parallel mode, the distribution of engine torque and motor torque is determined based on the current vehicle speed, driver's required torque, battery state of charge, equivalent factor, and constraints of the engine, motor, and battery, so as to minimize the equivalent fuel consumption value in parallel mode.

4. The method of claim 2, wherein, The global mode evaluation unit calculates the equivalent fuel consumption value for each operating mode, specifically including: For each candidate operating mode in pure electric mode, series mode and parallel mode, the corresponding equivalent fuel consumption value is calculated under a unified equivalent fuel consumption function framework. The equivalent fuel consumption function includes an engine fuel consumption term, a battery energy exchange equivalent term, and a penalty term. The battery energy exchange equivalent term is determined based on battery power and equivalent factor. The battery power is used to characterize the battery charge and discharge state, and the battery discharge state corresponds to positive power, while the battery charging state corresponds to negative power. Within the framework of the unified equivalent fuel consumption function, the pure electric mode, series mode, and parallel mode are solved under their respective constraints, and the working mode with the minimum equivalent fuel consumption value is selected as the global optimal mode.

5. The method of claim 1, wherein, The state management mechanism includes: Request status: Entered after generating a mode switching request, while maintaining the current working mode unchanged, and sending a switching command to the mode switching execution unit; Confirmation status: Wait for the switching status signal from the receiving mode switching execution unit, and set the preset timeout threshold; Completion status: When a switching completion signal is received within the preset timeout threshold, the current working mode is updated to the target mode, and the intermediate request status is cleared; Rollback state: If a switching completion signal is not received or a switching failure signal is received after the preset timeout threshold is exceeded, the mode switching request is canceled and the original working mode is maintained; During the state transition process, the optimal torque distribution parameters are always generated based on the current operating mode.

6. The method of claim 1, wherein, The power demand mode includes multiple SOC hysteresis modes, each SOC hysteresis mode has an entry threshold and an exit threshold, and the entry threshold and the exit threshold are different; at least one SOC hysteresis mode is provided with multiple vehicle speed sub-regions. The vehicle speed sub-region includes a low-speed sub-region, a medium-speed sub-region, and a high-speed sub-region; Different charging tendency, discharging tendency, or battery maintenance tendency correspond to different vehicle speed sub-regions, and the charging tendency, discharging tendency, or battery maintenance tendency is achieved by at least one of the following: equivalent factor, active power generation permission, active power generation upper limit, engine start-stop penalty parameter, and NVH penalty parameter.

7. A hybrid vehicle energy management system based on a separate ECMS and SOC-vehicle speed coupled power dispatching, characterized in that, include: The data acquisition module is used to acquire vehicle operating parameters, which include at least the battery state of charge, vehicle speed, current operating mode, and driver torque requirements. The equivalent factor and constraint parameter determination module is used to determine the SOC hysteresis power demand pattern based on the battery state of charge and the SOC hysteresis threshold, determine the vehicle speed sub-region based on the vehicle speed, and determine the equivalent factor and the constraint parameters corresponding to the equivalent factor based at least on the joint state formed by the SOC hysteresis power demand pattern and the vehicle speed sub-region. The separate optimization calculation module is configured to calculate the optimal torque distribution parameters under the current working mode and the global optimal mode selection across multiple candidate working modes based on the equivalent factor, the constraint parameters and the equivalent fuel consumption strategy. The command output module is used to output the optimal torque distribution parameters as a real-time drive command to the vehicle power system. The switching request generation module is used to generate a mode switching request when the globally optimal mode selection is inconsistent with the current working mode; The status management module is configured to process the mode switching request, update the working mode after receiving the switching completion signal from the mode switching execution unit, and revert to the original working mode if the switching fails. The global optimal mode selection is used only to generate the mode switching request, and is not directly used to output real-time driving commands.

8. A vehicle characterized by comprising: This includes the hybrid vehicle energy management system based on a separate ECMS and SOC-vehicle speed coupled power dispatching as described in claim 7.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1-6.

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