Self-learning method and system for optimal economic curve of series power generation in hybrid electric vehicles

Abstract

This invention discloses a self-learning method and system for the optimal economic curve of series power generation in hybrid electric vehicles, relating to the field of hybrid vehicle power control technology. The method includes: adding a time-varying test torque to the target torque of an engine operating at its operating point on a preset optimal economic curve, so that the engine adjusts its time-varying test operating point on the target isopower line based on the final torque; obtaining the time-varying fuel consumption rate of the engine at the time-varying test operating point; determining the minimum fuel consumption rate from the time-varying fuel consumption rates, and determining the test operating point of the engine corresponding to the minimum value; and performing self-learning correction on the preset optimal economic curve based on the test operating point corresponding to the minimum value to obtain the corrected optimal economic curve for the hybrid vehicle. This invention alleviates the technical problem in existing technologies where a fixed optimal economic curve cannot guarantee optimal energy consumption.

Description

Technical Field

[0001] This invention relates to the field of power control technology for hybrid vehicles, specifically to a self-learning method and system for the optimal economic curve of series power generation in hybrid vehicles. Background Technology

[0002] Existing series hybrid electric vehicles use a fixed optimal economic curve fitted to the universal characteristic curve of the engine and the efficiency distribution of the motor at various operating points during the series power generation process. This curve serves as the target operating point for the engine under various power generation demands in series mode. However, the universal characteristics of the engine and the efficiency distribution of the motor drive are usually subject to deviations and changes due to manufacturing variations and external environmental influences. Therefore, a fixed optimal economic curve cannot guarantee optimal energy consumption. Summary of the Invention

[0003] The purpose of this invention is to provide a self-learning method and system for the optimal economic curve of series power generation in hybrid electric vehicles in order to solve at least one of the above-mentioned technical problems.

[0004] In a first aspect, embodiments of the present invention provide a self-learning method for the optimal economic curve of a hybrid vehicle's series power generation, applied to a hybrid vehicle; the hybrid vehicle includes a generator and an engine operating in series; the method includes: adding a time-varying test torque to the target torque of the engine operating at a preset optimal economic curve, so that the engine adjusts its time-varying test operating point on a target isopower line based on the final torque; the final torque is the operating torque calculated based on the target torque and the test torque; the test operating point includes the final torque and the engine speed at the final torque; the target isopower line is the curve of the engine's torque versus speed when the generator generates a target power; obtaining the time-varying fuel consumption rate of the engine at the time-varying test operating point; determining the minimum value of the fuel consumption rate from the time-varying fuel consumption rates, and determining the test operating point of the engine corresponding to the minimum value; and performing self-learning correction on the preset optimal economic curve based on the test operating point corresponding to the minimum value to obtain the corrected optimal economic curve of the hybrid vehicle.

[0005] Furthermore, the range of the test torque is between a first torque and a second torque; the first torque is less than the second torque.

[0006] Furthermore, the test torque changes over time in the following manner: increasing from 0 to the second torque at a preset rate of change, then decreasing from the second torque to the first torque at the preset rate of change, and finally increasing from the first torque back to 0 at the preset rate of change.

[0007] Furthermore, the first torque is -10 Nm, and the second torque is 10 Nm.

[0008] Furthermore, the final torque and the engine speed at the final torque satisfy the following formula: EngSpd=9550*P / Tq; where Tq is the final torque, P is the target power generation, and EngSpd is the engine speed at the final torque.

[0009] Secondly, embodiments of the present invention also provide a self-learning system for the optimal economic curve of series power generation in hybrid electric vehicles, applied to hybrid electric vehicles; the hybrid electric vehicle includes a generator and an engine operating in series; it includes: a testing module, an acquisition module, a determination module, and a learning module; wherein, the testing module is used to add a time-varying test torque to the target torque of the engine operating at a preset optimal economic curve operating point, so that the engine adjusts the time-varying test operating point on the target isopower line based on the final torque; the final torque is the operating torque calculated based on the target torque and the test torque; the test operating point includes the final torque. The engine speed at the final torque; the target isopower line is the curve showing the change in engine torque with engine speed when the generator is generating power at the target power; the acquisition module is used to acquire the time-varying fuel consumption rate of the engine at the time-varying test operating point; the determination module is used to determine the minimum value of the time-varying fuel consumption rate and the test operating point of the engine corresponding to the minimum value; the learning module is used to perform self-learning correction on the preset optimal economic curve based on the test operating point corresponding to the minimum value to obtain the corrected optimal economic curve of the hybrid vehicle.

[0010] Furthermore, the range of the test torque is between a first torque and a second torque; the first torque is less than the second torque.

[0011] Furthermore, the test torque changes over time in the following manner: increasing from 0 to the second torque at a preset rate of change, then decreasing from the second torque to the first torque at the preset rate of change, and finally increasing from the first torque back to 0 at the preset rate of change.

[0012] Furthermore, the first torque is -10 Nm, and the second torque is 10 Nm.

[0013] Furthermore, the final torque and the engine speed at the final torque satisfy the following formula: EngSpd=9550*P / Tq; where Tq is the final torque, P is the target power generation, and EngSpd is the engine speed at the final torque.

[0014] This invention provides a self-learning method and system for the optimal economic curve of series power generation in hybrid electric vehicles. By increasing the test torque of the engine, the vehicle can operate on the corrected optimal economic curve at various power generation levels. This alleviates the problems of engine universal characteristic dispersion and motor efficiency distribution dispersion, as well as the technical problem that the fixed optimal economic curve in the prior art cannot guarantee optimal energy consumption. Attached Figure Description

[0015] The accompanying drawings, which form part of this specification, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0016] Figure 1 A flowchart illustrating a self-learning method for the optimal economic curve of series power generation in a hybrid vehicle, provided in an embodiment of the present invention;

[0017] Figure 2 A schematic diagram of the curve of test torque changing over time provided for an embodiment of the present invention;

[0018] Figure 3 A schematic diagram illustrating the correction of a preset optimal economic curve provided in an embodiment of the present invention;

[0019] Figure 4 This is a schematic diagram of a self-learning system for the optimal economic curve of series power generation in a hybrid vehicle, provided in an embodiment of the present invention. Detailed Implementation

[0020] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0021] The following detailed description is exemplary and intended to provide further detailed explanation of the invention. Unless otherwise specified, all technical terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this invention is for describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention.

[0022] Example 1

[0023] Figure 1This is a flowchart illustrating a self-learning method for the optimal economic curve of series power generation in a hybrid electric vehicle, according to an embodiment of the present invention. The method is applied to a hybrid electric vehicle; wherein the hybrid electric vehicle includes a generator and an engine operating in series. Figure 1 As shown, the method specifically includes the following steps:

[0024] Step S102: At the target torque of the engine operating at the preset optimal economic curve, a test torque that varies with time is added, so that the engine adjusts the test operating point that varies with time on the target isopower line based on the final torque; the final torque is the operating torque calculated based on the target torque and the test torque; the test operating point includes the final torque and the engine speed at the final torque; the target isopower line is the curve of the engine torque changing with the speed when the generator is generating power at the target power.

[0025] Step S104: Obtain the time-varying fuel consumption rate of the engine at the test operating point that varies with time.

[0026] Step S106: Determine the minimum value of the fuel consumption rate from the fuel consumption rate that changes over time, and determine the test operating point of the engine corresponding to the minimum value.

[0027] Step S1008: Based on the test operating point corresponding to the minimum value, perform self-learning correction on the preset optimal economic curve to obtain the corrected optimal economic curve for the hybrid vehicle.

[0028] Preferably, in this embodiment of the invention, the range of variation of the test torque is between a first torque and a second torque; the first torque is less than the second torque.

[0029] Preferably, the test torque changes over time in the following manner: increasing from 0 to a second torque at a preset rate of change, then decreasing from the second torque to a first torque at a preset rate of change, and finally increasing from the first torque back to 0 at a preset rate of change.

[0030] Optionally, the first torque is -10 Nm and the second torque is 10 Nm.

[0031] Figure 2 This is a schematic diagram of the curve showing the change of test torque over time according to an embodiment of the present invention. Figure 2 As shown, the test torque varies within ±10 Nm.

[0032] Specifically, when the hybrid vehicle is running stably under series conditions, the load of the high and low voltage power supply of the vehicle does not change significantly, the real-time current of the battery is stable, the engine status is stable and there are no factors such as diagnostics affecting fuel economy, and the engine coolant temperature is stable.

[0033] Specific operation: The engine operates at its operating point on the original optimal economic curve (i.e., the preset optimal economic curve mentioned above). At this point, a slowly varying torque (approximately ±10 Nm) is added to the engine's target torque. Figure 2 As shown, the target generator speed is calculated based on the current demand for power generation and the engine's final target torque, thereby ensuring that the generator's power generation remains constant.

[0034] Specifically, the final torque and the engine speed at the final torque satisfy the following formula:

[0035] EngSpd = 9550 * P / Tq;

[0036] Where Tq is the final torque, P is the target power generation, and EngSpd is the engine speed at the final torque.

[0037] Figure 3 This is a schematic diagram illustrating a correction of a preset optimal economic curve provided by an embodiment of the present invention. Figure 3 As shown, the engine's operating point moves around the original optimal economic curve on the isopower line as the engine's torque increases or decreases, such as... Figure 3 Within the boxed area, the engine's real-time fuel consumption rate is searched and compared. The engine operating point (engine torque and speed) at which the fuel consumption rate is minimized is recorded and stored as the next operating point for the entire vehicle at that power generation capacity. After the optimal economic curves for each power generation capacity have been corrected and learned, a system like this is formed. Figure 3 The solid line represents the optimal economic curve.

[0038] As described above, the embodiments of the present invention provide a self-learning method for the optimal economic curve of series power generation in hybrid electric vehicles. By increasing the test torque of the engine, the vehicle can operate on the corrected optimal economic curve at various power generation levels. This alleviates the problems of engine universal characteristic dispersion and motor efficiency distribution dispersion, as well as the technical problem that the fixed optimal economic curve in the prior art cannot guarantee optimal energy consumption.

[0039] Example 2

[0040] Figure 4 This is a schematic diagram of a self-learning system for the optimal economic curve of series power generation in a hybrid vehicle, according to an embodiment of the present invention. The system is applied to a hybrid vehicle; wherein the hybrid vehicle includes a generator and an engine operating in series. Figure 4 As shown, the system includes: a testing module 10, an acquisition module 20, a determination module 30, and a learning module 40.

[0041] Specifically, the test module 10 is used to add a time-varying test torque to the target torque of the engine operating at the operating point on the preset optimal economic curve, so that the engine adjusts the time-varying test operating point on the target isopower line based on the final torque; the final torque is the operating torque calculated based on the target torque and the test torque; the test operating point includes the final torque and the engine speed at the final torque; the target isopower line is the curve of the engine torque changing with the speed when the generator is generating power at the target power.

[0042] The acquisition module 20 is used to acquire the time-varying fuel consumption rate of the engine at the test operating point that varies over time.

[0043] The determination module 30 is used to determine the minimum value of the fuel consumption rate in the time-varying fuel consumption rate, and to determine the test operating point of the engine corresponding to the minimum value.

[0044] Learning module 40 is used to perform self-learning correction on the preset optimal economic curve based on the test operating point corresponding to the minimum value, so as to obtain the corrected optimal economic curve of the hybrid vehicle.

[0045] Preferably, the range of the test torque is between a first torque and a second torque; the first torque is less than the second torque.

[0046] Preferably, the test torque changes over time in the following manner: increasing from 0 to a second torque at a preset rate of change, then decreasing from the second torque to a first torque at a preset rate of change, and finally increasing from the first torque back to 0 at a preset rate of change.

[0047] Preferably, the first torque is -10 Nm and the second torque is 10 Nm.

[0048] Preferably, the final torque and the engine speed at the final torque satisfy the following formula:

[0049] EngSpd = 9550 * P / Tq;

[0050] Where Tq is the final torque, P is the target power generation, and EngSpd is the engine speed at the final torque.

[0051] As is known from common technical knowledge, this invention can be implemented through other embodiments that do not depart from its spirit or essential characteristics. Therefore, the disclosed embodiments described above are merely illustrative in all respects and are not the only ones. All modifications within the scope of this invention or its equivalents are included in this invention.

[0052] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0053] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0054] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0055] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0056] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A self-learning method for the optimal economic curve of series power generation in hybrid electric vehicles, characterized in that, Applied to hybrid vehicles; the hybrid vehicle includes a generator and an engine operating in series; including: At the target torque of an engine operating at its preset optimal economic curve, a time-varying test torque is added to adjust the engine's time-varying test operating point on the target isopower line based on the final torque. The final torque is the operating torque calculated based on the target torque and the test torque. The test operating point includes the final torque and the engine speed at the final torque. The target isopower line is the curve showing the engine's torque versus speed when the generator is generating power at the target output. Obtain the time-varying fuel consumption rate of the engine at the time-varying test operating point; Among the fuel consumption rates that vary over time, a minimum value of the fuel consumption rate is determined, and the test operating point of the engine corresponding to the minimum value is determined; Based on the test operating point corresponding to the minimum value, the preset optimal economic curve is self-learned and corrected to obtain the corrected optimal economic curve of the hybrid vehicle.

2. The method according to claim 1, characterized in that, The range of the test torque is between a first torque and a second torque; the first torque is less than the second torque.

3. The method according to claim 2, characterized in that, The test torque changes over time in the following manner: increasing from 0 to the second torque at a preset rate of change, then decreasing from the second torque to the first torque at the preset rate of change, and finally increasing from the first torque back to 0 at the preset rate of change.

4. The method according to claim 2 or 3, characterized in that, The first torque is -10 Nm, and the second torque is 10 Nm.

5. The method according to claim 1, characterized in that, The final torque and the engine speed at the final torque satisfy the following formula: EngSpd = 9550 * P / Tq; Where Tq is the final torque, P is the target power generation, and EngSpd is the engine speed at the final torque.

6. A self-learning system for the optimal economic curve of series power generation in hybrid electric vehicles, characterized in that, Applied to hybrid vehicles; the hybrid vehicle includes a generator and an engine operating in series; comprising: a testing module, an acquisition module, a determination module, and a learning module; wherein, The testing module is used to add a time-varying test torque to the target torque of the engine operating at its operating point on a preset optimal economic curve, so that the engine adjusts its time-varying test operating point on the target isopower line based on the final torque; the final torque is the operating torque calculated based on the target torque and the test torque; the test operating point includes the final torque and the engine speed at the final torque; the target isopower line is the curve showing the change of the engine torque with speed when the generator is generating power at the target output power. The acquisition module is used to acquire the time-varying fuel consumption rate of the engine at the time-varying test operating point. The determining module is used to determine the minimum value of the fuel consumption rate among the fuel consumption rates that change over time, and to determine the test operating point of the engine corresponding to the minimum value. The learning module is used to perform self-learning correction on the preset optimal economic curve based on the test operating point corresponding to the minimum value, so as to obtain the corrected optimal economic curve of the hybrid vehicle.

7. The system according to claim 6, characterized in that, The range of the test torque is between a first torque and a second torque; the first torque is less than the second torque.

8. The system according to claim 7, characterized in that, The test torque changes over time in the following manner: increasing from 0 to the second torque at a preset rate of change, then decreasing from the second torque to the first torque at the preset rate of change, and finally increasing from the first torque back to 0 at the preset rate of change.

9. The system according to claim 7 or 8, characterized in that, The first torque is -10 Nm, and the second torque is 10 Nm.

10. The system according to claim 6, characterized in that, The final torque and the engine speed at the final torque satisfy the following formula: EngSpd = 9550 * P / Tq; Where Tq is the final torque, P is the target power generation, and EngSpd is the engine speed at the final torque.

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