WO2015096575A1 - 海拔修正系数获取方法和装置 - Google Patents

海拔修正系数获取方法和装置 Download PDF

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Publication number
WO2015096575A1
WO2015096575A1 PCT/CN2014/092042 CN2014092042W WO2015096575A1 WO 2015096575 A1 WO2015096575 A1 WO 2015096575A1 CN 2014092042 W CN2014092042 W CN 2014092042W WO 2015096575 A1 WO2015096575 A1 WO 2015096575A1
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Prior art keywords
correction coefficient
self
altitude correction
learning
pressure sensor
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PCT/CN2014/092042
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English (en)
French (fr)
Inventor
祁克光
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奇瑞汽车股份有限公司
芜湖普威技研有限公司
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Application filed by 奇瑞汽车股份有限公司, 芜湖普威技研有限公司 filed Critical 奇瑞汽车股份有限公司
Priority to BR112016013742-6A priority Critical patent/BR112016013742B1/pt
Priority to RU2016125554A priority patent/RU2667891C2/ru
Priority to US15/105,953 priority patent/US10215122B2/en
Publication of WO2015096575A1 publication Critical patent/WO2015096575A1/zh

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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D41/00—Electrical control of supply of combustible mixture or its constituents
    • F02D41/24—Electrical control of supply of combustible mixture or its constituents characterised by the use of digital means
    • F02D41/2406—Electrical control of supply of combustible mixture or its constituents characterised by the use of digital means using essentially read only memories
    • F02D41/2425—Particular ways of programming the data
    • F02D41/2429—Methods of calibrating or learning
    • F02D41/2451—Methods of calibrating or learning characterised by what is learned or calibrated
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D41/00—Electrical control of supply of combustible mixture or its constituents
    • F02D41/02—Circuit arrangements for generating control signals
    • F02D41/021—Introducing corrections for particular conditions exterior to the engine
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D11/00—Arrangements for, or adaptations to, non-automatic engine control initiation means, e.g. operator initiated
    • F02D11/06—Arrangements for, or adaptations to, non-automatic engine control initiation means, e.g. operator initiated characterised by non-mechanical control linkages, e.g. fluid control linkages or by control linkages with power drive or assistance
    • F02D11/10—Arrangements for, or adaptations to, non-automatic engine control initiation means, e.g. operator initiated characterised by non-mechanical control linkages, e.g. fluid control linkages or by control linkages with power drive or assistance of the electric type
    • F02D11/106—Detection of demand or actuation
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D41/00—Electrical control of supply of combustible mixture or its constituents
    • F02D41/22—Safety or indicating devices for abnormal conditions
    • F02D41/222—Safety or indicating devices for abnormal conditions relating to the failure of sensors or parameter detection devices
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D41/00—Electrical control of supply of combustible mixture or its constituents
    • F02D41/24—Electrical control of supply of combustible mixture or its constituents characterised by the use of digital means
    • F02D41/2406—Electrical control of supply of combustible mixture or its constituents characterised by the use of digital means using essentially read only memories
    • F02D41/2425—Particular ways of programming the data
    • F02D41/2429—Methods of calibrating or learning
    • F02D41/2438—Active learning methods
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D41/00—Electrical control of supply of combustible mixture or its constituents
    • F02D41/24—Electrical control of supply of combustible mixture or its constituents characterised by the use of digital means
    • F02D41/2406—Electrical control of supply of combustible mixture or its constituents characterised by the use of digital means using essentially read only memories
    • F02D41/2425—Particular ways of programming the data
    • F02D41/2429—Methods of calibrating or learning
    • F02D41/2451—Methods of calibrating or learning characterised by what is learned or calibrated
    • F02D41/2474—Characteristics of sensors
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D2200/00—Input parameters for engine control
    • F02D2200/02—Input parameters for engine control the parameters being related to the engine
    • F02D2200/04—Engine intake system parameters
    • F02D2200/0406—Intake manifold pressure
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D2200/00—Input parameters for engine control
    • F02D2200/70—Input parameters for engine control said parameters being related to the vehicle exterior
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D2200/00—Input parameters for engine control
    • F02D2200/70—Input parameters for engine control said parameters being related to the vehicle exterior
    • F02D2200/703—Atmospheric pressure
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D41/00—Electrical control of supply of combustible mixture or its constituents
    • F02D41/22—Safety or indicating devices for abnormal conditions
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/10—Internal combustion engine [ICE] based vehicles
    • Y02T10/40—Engine management systems

Definitions

  • the invention relates to the field of automobiles, and in particular to a method and a device for acquiring an altitude correction coefficient.
  • the intake air volume of a car engine is an important parameter affecting the idle speed problem. Due to the vast demobilization in China, many places are in the plateau, such as the Northwest Plateau, Yunnan-Guizhou Plateau, and the Sichuan-Tibet Plateau. The air density decreases with the elevation. In order to ensure the normal operation of the vehicle at different altitudes, the intake air volume of the car engine The requirements must be corrected based on the altitude correction factor, so the accuracy of the altitude correction factor is critical.
  • the ECU (Electronic Control Unit) altitude correction coefficient can be obtained by modeling the self-learning algorithm.
  • the existing algorithm lacks the actual scene of the driving process, the acquired altitude correction coefficient is not accurate, and thus The engine intake air intake calculation is inaccurate. Therefore, there is a need for an ECU altitude correction coefficient acquisition method that can adapt to a complex driving environment.
  • an embodiment of the present invention provides a method and an apparatus for acquiring an altitude correction coefficient.
  • the technical solution is as follows:
  • an altitude correction coefficient acquisition method comprising:
  • the preset event includes a power-off event, a power-on event, and an abnormal power-down event;
  • an altitude correction coefficient acquisition apparatus comprising:
  • An initialization value obtaining module configured to acquire an altitude correction coefficient self-learning filter initialization value when a preset event occurs on the vehicle engine, where the preset event includes a power-off event, a power-on event, and an abnormal power-down event;
  • An enabling module configured to determine, according to the engine speed, the vehicle traveling speed, and status information of the designated device, whether the vehicle meets the preset self-learning enabling condition
  • the enabling module is further configured to enable the altitude correction coefficient self-learning filter if the vehicle meets a preset self-learning enable condition;
  • An input value determining module configured to determine an altitude correction coefficient self-learning filter input value according to at least a manifold pressure sensor and a working state of the stepping motor;
  • a self-learning module configured to self-learn the altitude correction coefficient by applying the altitude correction coefficient self-learning filter according to the altitude correction coefficient self-learning filter initialization value and the altitude correction coefficient self-learning filter input value Current altitude correction factor.
  • the acquisition of the initialization value takes into account the power-on self-learning function and the abnormal power-down condition processing, optimizes the engine speed processing scheme, and evades the use of altitude in the enabling process.
  • Learning conditions ultimately in determining the altitude correction factor self-learning filter
  • the acquisition of the altitude correction coefficient takes into account the actual scene of the driving process, making up for the inaccuracy of the altitude correction coefficient caused by the complexity of the actual scene, and improving the accuracy. Sex, which in turn improves idle stability.
  • Figure 1 is an overview of an altitude self-learning correction coefficient algorithm model
  • FIG. 2 is a flowchart of a method for acquiring an altitude correction coefficient according to an embodiment of the present invention
  • FIG. 3 is a schematic diagram of an initialization algorithm of an altitude correction coefficient self-learning filter according to an embodiment of the present invention
  • FIG. 4 is a schematic diagram of a basic logic of a self-learning enable condition according to an embodiment of the present invention.
  • FIG. 5 is a basic logic diagram of an altitude correction coefficient self-learning filter input algorithm according to an embodiment of the present invention.
  • FIG. 6 is a schematic structural diagram of an altitude self-learning correction coefficient calculation structure according to an embodiment of the present invention.
  • FIG. 8 is a schematic structural diagram of an apparatus for acquiring an altitude correction coefficient according to an embodiment of the present invention.
  • the algorithm model is introduced based on the schematic diagram of FIG. 1 : as shown in FIG. 1 , the algorithm model is mainly a low-pass filter, and the altitude correction coefficient is
  • the input of the learning filter has a filter time constant, an altitude correction coefficient self-learning filter input value, an altitude correction coefficient self-learning filter initialization value, and an altitude correction coefficient.
  • Self-learning filter initialization condition, altitude correction factor self-learning filter enable condition.
  • the altitude correction factor self-learning filter output is ambient pressure, and the output ambient pressure divided by the standard atmospheric pressure (1 atmosphere) is the altitude correction factor.
  • Output(new) is the filter output value
  • Output(old) is the last filter output value
  • Input is the altitude correction coefficient self-learning filter input value
  • dT is the filter calculation period
  • T is the filter time constant.
  • FIG. 2 is a flowchart of a method for acquiring an altitude correction coefficient according to an embodiment of the present invention. Referring to Figure 2, the method includes:
  • the self-learning filter initial value and the altitude correction coefficient self-learning filter input value are used according to the altitude correction coefficient, and the altitude correction coefficient self-learning filter is used to self-learn the altitude correction coefficient to obtain a current altitude correction coefficient.
  • the method provided by the embodiment of the present invention optimizes the engine speed processing scheme by taking advantage of the power-on self-learning function and the abnormal power-down condition processing in the initialization process of the altitude correction coefficient self-learning filter, and optimizes the engine speed processing scheme; In the process of circumventing some conditions that are not conducive to altitude self-learning, Finally, when determining the altitude correction factor self-learning filter input, the actual operation of the device will be taken into consideration.
  • the technical scheme adopted by the invention comprehensively considers the actual scene of the driving process in the process of acquiring the altitude correction coefficient, and compensates for the problem that the altitude correction coefficient is inaccurate due to the complicated actual scene, improves the accuracy, and improves the accuracy. Idle stability.
  • the initialization process of the altitude correction coefficient self-learning filter is introduced in conjunction with the elevation correction coefficient self-learning filter initialization algorithm logic diagram of FIG.
  • the altitude correction factor self-learning filter initialization takes into account many special circumstances, making the altitude self-learning coefficient more accurate. Each of the following conditions will cause the altitude correction factor self-learning filter to be initialized:
  • step 201 the process of obtaining the altitude correction coefficient self-learning filter initialization value when the vehicle engine generates a preset event is respectively described in step 201:
  • the process of obtaining the altitude correction coefficient from the initialization value of the learning filter can be regarded as the process of power-off initialization, and the power-off refers to the engine ignition key switch being turned off, that is, It is in the OFF state.
  • the power-off initialization refers to the first preset duration delay after the engine ignition key switch is turned off, and the engine speed is lower than the minimum recognition speed. If the manifold pressure sensor is determined to be faultless after the delay, the altitude correction coefficient self-learning The filter initialization value is the manifold pressure sensor value; if it is determined that the manifold pressure sensor is faulty, the altitude correction coefficient self-learning filter initialization value is the last altitude correction coefficient self-learning filter output value, that is, the last self-learning value (Pre-self-learning value in Figure 3).
  • the first preset duration may be set by a technician, which is not specifically limited in this embodiment of the present invention.
  • the initialization is performed by ensuring that the speed is reduced to zero by the rising edge delay as shown in Fig. 3.
  • the manifold pressure and the atmospheric pressure are the same, so the initialization value is the value from the manifold pressure sensor.
  • the last output value of the self-learning filter due to the altitude correction coefficient is the self-learning pressure value of the altitude during engine operation, which is the value closest to the ambient pressure at this time.
  • the initialization value is the altitude correction factor.
  • the last output value of the self-learning filter (which is stored in the ECU) remains unchanged.
  • the process of obtaining the altitude correction coefficient from the initialization value of the learning filter can be regarded as the process of power-on initialization, and the power-on refers to the engine ignition key switch being turned on, that is, It is in the ON state (can be determined by the ignition key switch state in Figure 3).
  • the altitude correction coefficient is the manifold pressure sensor value; if it is determined that the manifold pressure sensor is faulty, the altitude correction coefficient self-learning filter initialization value is the last altitude correction coefficient self-learning filter output value.
  • the second preset duration may be set by a technician, which is not specifically limited in this embodiment of the present invention.
  • the process of obtaining the altitude correction coefficient from the initialization value of the learning filter can be regarded as the process of abnormal power-down initialization, and the abnormal power-down initialization refers to the abnormal power-down flag position. Bit.
  • the altitude correction factor self-learning filter initialization value is the manifold pressure sensor value; Determine the manifold pressure sensor is fault-free, and the engine has the speed.
  • the altitude correction coefficient self-learning filter initialization value is 1 standard atmospheric pressure; if it is determined that the manifold pressure sensor is faulty, the altitude correction coefficient self-learning filter initialization value is 1 standard. Atmospheric pressure.
  • the advantage of adding an abnormal power-down self-learning strategy is that when the vehicle harness is poorly contacted or the battery power is unplugged artificially, the initialization error occurs and the vehicle malfunctions.
  • the manifold pressure at this time is very small. If the manifold pressure is used as the initial value, the calculation error of the altitude correction parameter is large. Therefore, considering the car use environment, the probability of abnormal power failure at high altitude is very low, and one standard atmospheric pressure is the most rational value of the wave filter initialization value.
  • the self-learning enable condition of the altitude correction coefficient self-learning filter is introduced.
  • the self-learning enabling condition considers many special circumstances to make the altitude self-learning coefficient more accurate. The following conditions will enable the altitude correction coefficient self-learning filter:
  • determining whether the vehicle satisfies the preset self-learning enable condition according to the engine speed, the vehicle traveling speed, and the status information of the designated device includes:
  • the engine speed is greater than the minimum recognition speed.
  • the vehicle travel speed is greater than the preset threshold (such as the vehicle speed threshold in Figure 4); the preset threshold can be set by the technician.
  • the preset threshold is 12 km/h to 15 km/h, and preferably, the preset threshold is 15 km/h.
  • the current altitude correction coefficient is less than 1, and is in the oil cut state (determined by the oil cut state flag in Figure 4) or in the idle state (determined by the idle state flag in Figure 4) but the vehicle speed is not faulty (by Figure 4) The speed of the vehicle is determined to be faulty);
  • the throttle position (such as the throttle opening shown in Figure 4) is greater than the altitude self-learning threshold (which may be the throttle position threshold), and the throttle position sensor is fault free (can be as shown in Figure 4) Throttle position sensor failure determination).
  • the acquisition of the altitude correction coefficient self-learning filter input value is introduced: when determining the altitude correction coefficient self-learning filter input value, consider some The actual operation of the equipment makes it possible to comprehensively consider the actual scene of the driving process for the acquisition of the altitude correction coefficient.
  • determining the altitude correction coefficient self-learning filter input value according to at least the operation state of the manifold pressure sensor and the stepping motor includes:
  • the input value of the altitude correction coefficient self-learning filter is 800hpa to 900hpa, preferably, the input value of the altitude correction coefficient self-learning filter is 850hpa.
  • Altitude correction factor Self-learning filter input selection 850hpa can take into account normal altitude and high altitude (mixed-loop closed-loop adjustment factor can be corrected by 25%).
  • the altitude correction coefficient self-learning filter input value is 1013hpa.
  • the two second preset conditions include:
  • the vehicle speed sensor has no fault, and the idle speed status flag is set, and the vehicle speed is greater than the vehicle speed threshold.
  • the altitude correction coefficient self-learning filter input is optimally selected from 1000hpa to 1100hpa.
  • the altitude correction coefficient self-learning filter input is optimally selected as 1013hpa.
  • the altitude correction factor self-learning filter input value is the manifold pressure divided by the throttle front-to-back pressure ratio.
  • the input of the altitude correction coefficient self-learning filter is the manifold pressure divided by the throttle front-to-back pressure ratio. In fact, this ratio is the pre-throttle pressure. When the pressure ratio before and after the throttle is relatively accurate, the pre-throttle pressure is close to the ambient pressure.
  • the case (6) is the calculation of the normal altitude correction coefficient self-learning filter input value.
  • the method provided by the embodiment of the present invention optimizes the engine speed processing scheme by taking advantage of the power-on self-learning function and the abnormal power-down condition processing in the initialization process of the altitude correction coefficient self-learning filter, and optimizes the engine speed processing scheme; In the process of energy, some conditions that are not conducive to altitude self-learning are avoided. Finally, when determining the altitude correction coefficient self-learning filter input, the actual operation of the equipment will be taken into consideration.
  • the technical scheme adopted by the invention comprehensively considers the actual scene of the driving process in the process of acquiring the altitude correction coefficient, and compensates for the problem that the altitude correction coefficient is inaccurate due to the complicated actual scene, improves the accuracy, and improves the accuracy. Idle stability.
  • FIG. 6 is a schematic structural diagram of calculating an altitude self-learning correction coefficient according to an embodiment of the present invention.
  • the above simulation process can be based on the structure shown in FIG. 6, and a specific calculation process is implemented in the ECU.
  • the structure includes an intake pipe, a throttle body, an intake manifold, and a manifold pressure sensor for detecting manifold pressure, the intake manifold being coupled to the engine.
  • FIG. 7 is a simulation result of an altitude self-learning correction coefficient algorithm model according to an embodiment of the present invention. Taking the altitude of 2500 meters above sea level as the experimental environment, the atmospheric pressure in the plain is 1013hpa, and after reaching the plateau of 2500 meters, the current atmospheric pressure can be calculated quickly at around 750hpa, and the altitude self-learning correction coefficient is atmospheric pressure divided by 1013hpa. .
  • FIG. 8 is a schematic structural diagram of an altitude correction coefficient acquiring apparatus according to an embodiment of the present invention.
  • the device includes:
  • the initialization value obtaining module 801 is configured to acquire an altitude correction coefficient self-learning filter initialization value when the vehicle engine generates a preset event, where the preset event includes a power-off event, a power-on event, and an abnormal power-down event;
  • the enabling module 802 is configured to determine, according to the engine speed, the vehicle traveling speed, and the status information of the designated device, whether the vehicle meets the preset self-learning enable condition;
  • the enabling module 802 is further configured to enable an altitude correction coefficient self-learning filter if the vehicle meets a preset self-learning enabling condition;
  • the input value determining module 803 is configured to determine an altitude correction coefficient self-learning filter input value according to at least the operation state of the manifold pressure sensor and the stepping motor;
  • the self-learning module 804 is configured to self-learn the altitude correction coefficient according to the altitude correction coefficient self-learning filter initialization value and the altitude correction coefficient self-learning filter input value, and obtain the current altitude. Correction factor.
  • the initialization value obtaining module 801 is configured to determine whether the manifold pressure sensor is faulty after the engine ignition key switch is turned off and the engine speed is lower than the minimum recognition speed, after the first preset duration delay;
  • the altitude correction coefficient self-learning filter initialization value is the manifold pressure sensor value
  • the altitude correction coefficient self-learning filter initialization value is the last altitude correction coefficient self-learning filter output value.
  • the initialization value obtaining module 801 is configured to determine whether the manifold pressure sensor is faulty when the engine ignition key switch is turned on, and the engine speed is lower than the minimum recognition speed, and the down time is greater than the second preset duration;
  • the altitude correction factor self-learning filter initialization value is the manifold pressure sensor value
  • the altitude correction coefficient self-learning filter initialization value is the last altitude correction coefficient self-learning filter output value.
  • the initialization value obtaining module 801 is configured to determine whether the manifold pressure sensor is faulty when the engine is abnormally powered down and the power is restored again;
  • the altitude correction coefficient self-learning filter initialization value is the manifold pressure sensor value
  • the altitude correction coefficient self-learning filter initialization value is 1 standard atmospheric pressure
  • the altitude correction factor self-learning filter initialization value is 1 standard atmosphere.
  • the enabling module 802 is configured to determine the vehicle when it is determined that the engine speed is greater than the minimum recognition speed, the vehicle traveling speed is greater than a preset threshold, and any one of the following plurality of first preset conditions is met. Meet the preset self-learning enable condition;
  • the plurality of first preset conditions include:
  • the manifold pressure sensor or stepper motor is faulty
  • the current altitude correction coefficient is less than 1, and is in the oil cut state or in the idle state but the vehicle speed is not faulty;
  • the throttle position is greater than the altitude self-learning threshold and the throttle position sensor is fault free.
  • the input value determining module 803 is configured to: when the manifold pressure sensor is faulty or the stepping motor is faulty, the input value of the altitude correction coefficient self-learning filter is 800 hpa to 900 hpa, preferably, the altitude correction coefficient is The input value of the learning filter is 850hpa;
  • the input value determining module 803 is further configured to: when the manifold pressure sensor and the stepping motor are both faultless, and the altitude correction coefficient is less than 1, and meet any one of the following two second preset conditions, the altitude correction coefficient at this time
  • the self-learning filter input is optimally selected from 1000hpa to 1100hpa.
  • the altitude correction coefficient self-learning filter input is optimally selected to be 1013hpa.
  • the two second preset conditions include: the vehicle is in a fuel cut state; the vehicle speed sensor has no fault, and the idle speed flag is set, and the vehicle speed is greater than the vehicle speed threshold;
  • the input value determining module 803 is further configured to: when none of the above conditions are satisfied, the altitude correction coefficient self-learning filter input value is a manifold pressure divided by a throttle front-to-back pressure ratio.
  • An embodiment of the present invention provides an altitude correction coefficient acquiring apparatus, where the apparatus includes:
  • a memory for storing processor executable instructions
  • the processor is configured to execute the following instructions:
  • an altitude correction coefficient self-learning filter initialization value when a preset event occurs on the vehicle engine, the preset event including a power-off event, a power-on event, and an abnormal power-down event;
  • the altitude correction coefficient self-learning filter is enabled
  • the altitude correction coefficient self-learning filter is used to self-learn the altitude correction coefficient to obtain the current altitude correction coefficient.
  • This processor is used to execute the following instructions:
  • the altitude correction coefficient self-learning filter initialization value is the manifold pressure sensor value
  • the altitude correction coefficient self-learning filter initialization value is the last altitude correction coefficient self-learning filter output value.
  • This processor is used to execute the following instructions:
  • the altitude correction factor self-learning filter initialization value is the manifold pressure sensor value
  • the altitude correction coefficient self-learning filter initialization value is the last altitude correction coefficient self-learning filter output value.
  • This processor is used to execute the following instructions:
  • the altitude correction coefficient self-learning filter initialization value is the manifold pressure sensor value
  • the altitude correction factor is self-learning.
  • the filter initialization value is 1 standard atmospheric pressure
  • the altitude correction factor self-learning filter initialization value is 1 standard atmosphere.
  • This processor is used to execute the following instructions:
  • the plurality of first preset conditions include:
  • the manifold pressure sensor or stepper motor is faulty
  • the current altitude correction coefficient is less than 1, and is in the oil cut state or in the idle state but the vehicle speed is not faulty;
  • the throttle position is greater than the altitude self-learning threshold and the throttle position sensor is fault free.
  • This processor is used to execute the following instructions:
  • the input value of the altitude correction coefficient self-learning filter is 800hpa to 900hpa;
  • the altitude correction coefficient self-learning filter input value is 1000 hpa to 1100 hpa;
  • the two second preset conditions include: the vehicle is in a fuel cut state; the vehicle speed sensor has no fault, and the idle speed flag is set, and the vehicle speed is greater than the vehicle speed threshold;
  • the altitude correction factor self-learning filter input value is the manifold pressure divided by the throttle front-to-back pressure ratio.
  • the device provided by the embodiment of the present invention optimizes the engine speed processing scheme by optimizing the power-on self-learning function and the abnormal power-down condition processing during the initialization process of the altitude correction coefficient self-learning filter, and is enabled.
  • the conditions of self-learning without altitude are avoided, and finally, when determining the altitude correction coefficient self-learning filter input, considering the actual operation of some equipments, the acquisition of the altitude correction coefficient takes into account the actual scene of the driving process. It compensates for the inaccuracy of the altitude correction coefficient caused by the complexity of the actual scene, improves the accuracy, and further improves the idle stability.
  • non-transitory computer readable storage medium comprising instructions, such as a memory comprising instructions executable by a processor of the apparatus to perform the above method.
  • the non-transitory computer readable storage medium may be a ROM, a RAM (Random Access Memory), a CD-ROM (Compact Disc Read-Only Memory), a magnetic tape, a floppy disk, and an optical data storage. Equipment, etc.
  • a non-transitory computer readable storage medium when instructions in the storage medium are executed by a processor of a device, to enable a device to perform an altitude correction coefficient acquisition method, the method comprising:
  • an altitude correction coefficient self-learning filter initialization value when a preset event occurs on the vehicle engine, the preset event including a power-off event, a power-on event, and an abnormal power-down event;
  • the altitude correction coefficient self-learning filter is enabled
  • the altitude correction coefficient self-learning filter is used to self-learn the altitude correction coefficient to obtain the current altitude correction coefficient.
  • the memory of the device further includes instructions for performing the following operations:
  • the altitude correction coefficient self-learning filter initialization value is the manifold pressure sensor value
  • the altitude correction coefficient self-learning filter initialization value is the last altitude correction coefficient self-learning filter output value.
  • the memory of the terminal further includes an instruction for performing the following operations:
  • the altitude correction factor self-learning filter initialization value is the manifold pressure sensor value
  • the altitude correction coefficient self-learning filter initialization value is the last altitude correction coefficient self-learning filter output value.
  • the memory of the terminal further includes an instruction for performing the following operations:
  • the altitude correction coefficient self-learning filter initialization value is the manifold pressure sensor value
  • the altitude correction coefficient self-learning filter initialization value is 1 standard atmospheric pressure
  • the altitude correction factor self-learning filter initialization value is 1 standard atmosphere.
  • the memory of the terminal further includes an instruction for performing the following operations:
  • the plurality of first preset conditions include:
  • the manifold pressure sensor or stepper motor is faulty
  • the current altitude correction coefficient is less than 1, and is in the oil cut state or in the idle state but the vehicle speed is not faulty;
  • the throttle position is greater than the altitude self-learning threshold and the throttle position sensor is fault free.
  • the end memory also contains instructions for performing the following operations:
  • the input value of the altitude correction coefficient self-learning filter is 800 hpa to 900 hpa.
  • the input value of the altitude correction coefficient self-learning filter is 850 hpa.
  • the altitude correction coefficient self-learning filter input is optimally selected as 1000hpa ⁇ 1100hpa, preferably, the altitude correction coefficient self-learning filter input is optimally selected as 1013hpa.
  • the two second preset conditions include: the vehicle is in a fuel cut state; the vehicle speed sensor has no fault, and the idle speed flag is set, and the vehicle speed is greater than the vehicle speed threshold;
  • the altitude correction factor self-learning filter input value is the manifold pressure divided by the throttle front-to-back pressure ratio.
  • the non-transitory computer readable storage medium provided by the embodiment of the present disclosure optimizes the engine speed by taking into account the power-on self-learning function and the abnormal power-down condition processing in the initialization process of the altitude correction coefficient self-learning filter.
  • the solution is processed, and the conditions for not using the altitude self-learning are avoided in the enabling process.
  • the acquisition of the altitude correction coefficient is integrated. Considering the actual scene of the driving process, it compensates for the inaccuracy of the altitude correction coefficient caused by the complexity of the actual scene, improves the accuracy, and improves the idle speed stability.
  • the altitude correction coefficient obtaining device provided by the above embodiment is only illustrated by the division of the above functional modules when the altitude correction coefficient is acquired. In actual applications, the functions may be assigned different functions according to needs. The module is completed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above.
  • the elevation correction coefficient acquisition device and the elevation correction coefficient acquisition method are provided in the same embodiment, and the specific implementation process is described in detail in the method embodiment, and details are not described herein again.

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Abstract

一种海拔修正系数获取方法，包括：当车辆发动机发生预设事件时，获取海拔修正系数自学习滤波器初始化值，所述预设事件包括下电事件、上电事件和异常掉电事件；根据所述发动机的转速、车辆行驶速度以及指定设备的状态信息，判断车辆是否满足预设自学习使能条件；如果车辆满足预设自学习使能条件，使能海拔修正系数自学习滤波器；至少根据歧管压力传感器以及步进电机的工作状态，确定海拔修正系数自学习滤波器输入值；根据海拔修正系数自学习滤波器初始化值和海拔修正系数自学习滤波器输入值，应用海拔修正系数自学习滤波器对海拔修正系数进行自学习，得到当前海拔修正系数。还公开了一种采用上述海拔修正系数获取方法的海拔修正系数获取装置。上述海拔修正系数获取方法和装置提高了修正系数的准确性和怠速稳定性。

Description

海拔修正系数获取方法和装置
本申请要求于2013年12月23日提交中国专利局、申请号为201310719383.3、发明名称为“海拔修正系数获取方法和装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本发明涉及汽车领域，特别涉及一种海拔修正系数获取方法和装置。
背景技术
在汽车电子控制领域，汽车发动机工作的进气量是影响怠速问题的一个重要参数。由于我国复员辽阔，很多地方处于高原地带，如西北高原、云贵高原、川藏高原等，空气密度随海拔的升高而减小，为了保证车辆在不同的海拔正常运行，汽车发动机工作进气量需求务必需要基于海拔修正系数进行修正，因此，海拔修正系数的准确性至关重要。
目前ECU(Electronic Control Unit，电子控制单元)海拔修正系数可以通过对自学习算法进行建模获得，然而，由于现有算法缺乏对行车过程实际场景的考虑，所获取的海拔修正系数不准确，进而使得发动机工作进气量计算不准确。因此，亟需一种能够适应复杂行车环境的ECU海拔修正系数获取方法。
发明内容
为了解决现有技术的问题，本发明实施例提供了一种海拔修正系数获取方法和装置。所述技术方案如下：
一方面，提供了一种海拔修正系数获取方法，所述方法包括：
当车辆发动机发生预设事件时，获取海拔修正系数自学习滤波器初始化值， 所述预设事件包括下电事件、上电事件和异常掉电事件；
根据所述发动机的转速、车辆行驶速度以及指定设备的状态信息，判断车辆是否满足预设自学习使能条件；
如果所述车辆满足预设自学习使能条件，使能所述海拔修正系数自学习滤波器；
至少根据歧管压力传感器以及步进电机的工作状态，确定海拔修正系数自学习滤波器输入值；
根据所述海拔修正系数自学习滤波器初始化值和所述海拔修正系数自学习滤波器输入值，应用所述海拔修正系数自学习滤波器对海拔修正系数进行自学习，得到当前海拔修正系数。
另一方面，提供了一种海拔修正系数获取装置，所述装置包括：
初始化值获取模块，用于当车辆发动机发生预设事件时，获取海拔修正系数自学习滤波器初始化值，所述预设事件包括下电事件、上电事件和异常掉电事件；
使能模块，用于根据所述发动机的转速、车辆行驶速度以及指定设备的状态信息，判断车辆是否满足预设自学习使能条件；
所述使能模块还用于如果所述车辆满足预设自学习使能条件，使能所述海拔修正系数自学习滤波器；
输入值确定模块，用于至少根据歧管压力传感器以及步进电机的工作状态，确定海拔修正系数自学习滤波器输入值；
自学习模块，用于根据所述海拔修正系数自学习滤波器初始化值和所述海拔修正系数自学习滤波器输入值，应用所述海拔修正系数自学习滤波器对海拔修正系数进行自学习，得到当前海拔修正系数。
本发明实施例提供的技术方案带来的有益效果是：
通过在海拔修正系数自学习滤波器初始化过程中，对初始化值的获取考虑到上电自学习功能和异常掉电情况处理，优化发动机转速处理方案，并在使能过程中规避了不利用海拔自学习的条件，最终在确定海拔修正系数自学习滤波 器输入时，考虑到一些设备的实际运转情况，使得对于海拔修正系数的获取，综合考虑了行车过程的实际场景，弥补了由于实际场景复杂而造成的海拔修正系数不准确的问题，提高了准确性，进而提高了怠速稳定性。
附图说明
为了更清楚地说明本发明实施例中的技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是海拔自学习修正系数算法模型概图；
图2是本发明实施例提供的一种海拔修正系数获取方法的流程图；
图3是本发明实施例提供的海拔修正系数自学习滤波器初始化算法逻辑示意图；
图4是本发明实施例提供的自学习使能条件基本逻辑示意图；
图5是本发明实施例提供的海拔修正系数自学习滤波器输入算法基本逻辑示意图；
图6是本发明实施例提供的海拔自学习修正系数计算结构示意图；
图7是本发明实施例提供的海拔自学习修正系数算法模型仿真结果；
图8是本发明实施例提供的一种海拔修正系数获取装置结构示意图。
具体实施方式
为使本发明的目的、技术方案和优点更加清楚，下面将结合附图对本发明实施方式作进一步地详细描述。
为了便于对本发明提供的ECU海拔自学习修正系数算法模型的理解，下面基于图1的示意图，对算法模型进行介绍：如图1所示，算法模型主要是一个低通滤波器，海拔修正系数自学习滤波器的输入有滤波时间常数、海拔修正系数自学习滤波器输入值、海拔修正系数自学习滤波器初始化值、海拔修正系数 自学习滤波器初始化条件、海拔修正系数自学习滤波器使能条件。海拔修正系数自学习滤波器输出为环境压力，输出的环境压力除以标准大气压力(1个大气压)就为海拔修正系数。
海拔修正系数自学习滤波器的计算公式：
滤波器的计算公式：
Output(new)＝Output(old)+{Input-Output(old)}×dT/T，
其中，
Output(new)为本次滤波器输出值，Output(old)为上一次滤波器输出值，Input为海拔修正系数自学习滤波器输入值，dT为滤波器计算周期，T为滤波时间常数。
图2是本发明实施例提供的一种海拔修正系数获取方法的流程图。参见图2，所述方法包括：
201、当车辆发动机发生预设事件时，获取海拔修正系数自学习滤波器初始化值，该预设事件包括下电事件、上电事件和异常掉电事件；
202、根据该发动机的转速、车辆行驶速度以及指定设备的状态信息，判断车辆是否满足预设自学习使能条件；
203、如果该车辆满足预设自学习使能条件，使能海拔修正系数自学习海拔修正系数自学习滤波器；
204、至少根据歧管压力传感器以及步进电机的工作状态，确定海拔修正系数自学习滤波器输入值；
205、根据该海拔修正系数自学习滤波器初始化值和该海拔修正系数自学习滤波器输入值，应用该海拔修正系数自学习滤波器对海拔修正系数进行自学习，得到当前海拔修正系数。
本发明实施例提供的方法，通过在海拔修正系数自学习滤波器初始化过程中，对初始化值的获取考虑到上电自学习功能和异常掉电情况处理，优化了发动机转速处理方案；并且在使能过程中规避了一些不利于海拔自学习的条件， 最终，在确定海拔修正系数自学习滤波器输入时，将考虑设备的实际运转情况纳入考虑范围内。本发明所采用的技术方案，在海拔修正系数的获取过程中，综合考虑了行车过程的实际场景，弥补了由于实际场景复杂而造成的海拔修正系数不准确的问题，提高了准确性，进而提高了怠速稳定性。
首先，结合图3的海拔修正系数自学习滤波器初始化算法逻辑示意图，对海拔修正系数自学习滤波器的初始化过程进行介绍。海拔修正系数自学习滤波器初始化考虑诸多特殊情况，使海拔自学习系数更加准确，满足下列每种情况都会使海拔修正系数自学习滤波器进行初始化：
也即是，基于上述下电事件、上电事件和异常掉电事件，分别对步骤201“当车辆发动机发生预设事件时，获取海拔修正系数自学习滤波器初始化值”的过程进行说明：
(1)预设事件为下电事件时，可将该获取海拔修正系数自学习滤波器初始化值的过程看做是下电初始化的过程，该下电是指发动机点火钥匙开关关闭，也即是处于OFF状态。
该下电初始化是指当发动机点火钥匙开关关闭，且发动机转速低于最小识别转速后，经过第一预设时长延时，如果经过延时后确定歧管压力传感器无故障，海拔修正系数自学习滤波器初始化值为歧管压力传感器值；如果确定歧管压力传感器有故障，海拔修正系数自学习滤波器初始化值为上一次海拔修正系数自学习滤波器输出值，也即是上一次自学习值(图3中的前自学习值)。其中，该第一预设时长可以由技术人员设置，本发明实施例对此不作具体限定。
对于第(1)种情况，当发动机停机后，随着发动机转速的下降，发动机转速低于最小识别转速，用于标识最小识别转速的标志位由0变为1，上升沿延迟t秒(可通过如图3所示的上升沿延迟进行)，确保转速降为0才进行初始化，此时歧管压力和大气压力相同，所以初始化值为来自歧管压力传感器的值。而当歧管压力传感器出现故障的时候，由于海拔修正系数自学习滤波器的上一次输出值是发动机运行中海拔自学习压力值，是最接近此时环境压力的值，因此， 初始化值为海拔修正系数自学习滤波器上一次的输出值(该输出值存储于ECU中)保持不变。
(2)预设事件为上电事件时，可将该获取海拔修正系数自学习滤波器初始化值的过程看做是上电初始化的过程，该上电是指发动机点火钥匙开关开启，也即是处于ON状态(可通过图3中的点火钥匙开关状态确定)。
当发动机点火钥匙开关开启，且发动机转速低于最小识别转速，且停机时间大于第二预设时长(可通过如图3的计时器实现)时，如果确定歧管压力传感器无故障，海拔修正系数自学习滤波器初始化值为歧管压力传感器值；如果确定歧管压力传感器有故障，海拔修正系数自学习滤波器初始化值为上一次海拔修正系数自学习滤波器输出值。
其中，第二预设时长可以由技术人员设置，本发明实施例对此不作具体限定。
对于第(2)种情况，在海拔修正系数自学习滤波器初始化过程中考虑到上电初始化可以避免车辆拖运过程中，由于海拔的差异导致的起动和怠速问题，且通过确定停机时间大于一定的值，可以确保歧管压力和环境压力基本一致，可避免快速起动偏差问题。
(3)预设事件为异常掉电事件时，可将该获取海拔修正系数自学习滤波器初始化值的过程看做是异常掉电初始化的过程，异常掉电初始化，是指异常掉电标志位置位。
当发动机异常掉电并再次恢复供电时，确定歧管压力传感器是否故障；如果确定歧管压力传感器无故障，且发动机无转速，海拔修正系数自学习滤波器初始化值为歧管压力传感器值；如果确定歧管压力传感器无故障，且发动机有转速，海拔修正系数自学习滤波器初始化值为1个标准大气压；如果确定歧管压力传感器有故障，海拔修正系数自学习滤波器初始化值为1个标准大气压。
对于第(3)种情况，增加异常掉电自学习策略的好处是：当车辆线束接触不良或者人为的把电池电源拔掉，导致初始化错误，车辆运行故障。
而考虑是否有发动机转速是因为，如果线束接触不良，且发动机处于运行 中，此时的歧管压力很小，如果把歧管压力作为初始化值，对海拔修正参数的计算误差较大。因此，考虑汽车使用环境在高海拔出现异常掉电的几率很低，1个标准大气压是波器初始化值最合理化的值。
其次，结合图4的自学习使能条件基本逻辑示意图，对海拔修正系数自学习滤波器的自学习使能条件进行介绍。自学习使能条件考虑诸多特殊情况，使海拔自学习系数更加准确，满足下列情况都会使能海拔修正系数自学习滤波器：
也即是，根据该发动机的转速、车辆行驶速度以及指定设备的状态信息，判断车辆是否满足预设自学习使能条件包括：
判断车辆是否同时满足以下三个条件：
(1)发动机转速大于最小识别转速。
(2)车辆行驶速度大于预设门限值(如图4中的车速门限值)；该预设门限值可以由技术人员设置。如，该预设门限值为12km/h～15km/h，优选地，该预设门限值为15km/h。
(3)满足下列(3.1)-(3.3)中条件之一：
(3.1)歧管压力传感器(可由图4中的歧管压力传感器故障标识确定)或者步进电机有故障；
(3.2)当前海拔修正系数小于1，且处于断油状态(可由图4中的断油状态标志确定)或者处于怠速状态(可由图4中的怠速状态标志确定)但车速无故障(可由图4中的车速故障确定)；
(3.3)节气门位置(如图4中所示的节气门开度)大于海拔自学习门限值(可以为节气门位置门限值)，且节气门位置传感器无故障(可由图4中的节气门位置传感器故障确定)。
当同时满足上述三个条件时，确定该车辆满足预设自学习使能条件；
对于自学习使能条件，需要考虑到海拔自学习修正系数计算的准确性，还要考虑一些重要传感器损坏在初始化时出现的错误，以通过自学习算法进行修正，因此，需要考虑到一些重要的设备的实际状态。
其次，结合图5的海拔修正系数自学习滤波器输入算法基本逻辑示意图，对海拔修正系数自学习滤波器输入值的获取进行介绍：在确定海拔修正系数自学习滤波器输入值时，考虑到一些设备的实际运转情况，使得对于海拔修正系数的获取，综合考虑了行车过程的实际场景。
也即是，至少根据歧管压力传感器以及步进电机的工作状态，确定海拔修正系数自学习滤波器输入值包括：
(4)当歧管压力传感器有故障或者步进电机有故障的时候，海拔修正系数自学习滤波器的输入值为800hpa～900hpa，优选地，海拔修正系数自学习滤波器的输入值为850hpa。
对于第(4)种情况，当歧管压力传感器或者步进电机有故障的时候，歧管压力的计算和节气门前后压力比的计算就不可信。海拔修正系数自学习滤波器输入选择850hpa可以兼顾正常海拔和高海拔(混合气闭环调节系数可以修正25％)。
(5)当歧管压力传感器和步进电机都无故障，且海拔修正系数小于1，且满足下列两个第二预设条件中任一项时，海拔修正系数自学习滤波器输入值为1013hpa；
其中，该两个第二预设条件包括：
(5.1)车辆处于断油状态；
(5.2)车速传感器无故障，且怠速状态标志置位，且车速大于车速门限值。
对于第(5)种情况，如果车辆处于断油，或者车辆滑行怠速的时候，这两种情况下歧管真空度较低，用歧管压力除以节气门前后压力比计算节气门前压力作为输入偏差较大，此时海拔修正系数自学习滤波器输入最佳选择为1000hpa～1100hpa，优选地，海拔修正系数自学习滤波器输入最佳选择为1013hpa。
(6)当上述任一条件都不满足的时候，海拔修正系数自学习滤波器输入值为歧管压力除以节气门前后压力比。
对于第(6)种情况，当(4)和(5)的条件都不满足的时候，海拔修正系数自学习滤波器的输入为歧管压力除以节气门前后压力比。实际上这个比值就是节气门前压力，当节气门前后压力比比较准确的时候，节气门前压力就接近于环境压力。该第(6)种情况为正常的海拔修正系数自学习滤波器输入值的计算。
本发明实施例提供的方法，通过在海拔修正系数自学习滤波器初始化过程中，对初始化值的获取考虑到上电自学习功能和异常掉电情况处理，优化了发动机转速处理方案；并且在使能过程中规避了一些不利于海拔自学习的条件，最终，在确定海拔修正系数自学习滤波器输入时，将考虑设备的实际运转情况纳入考虑范围内。本发明所采用的技术方案，在海拔修正系数的获取过程中，综合考虑了行车过程的实际场景，弥补了由于实际场景复杂而造成的海拔修正系数不准确的问题，提高了准确性，进而提高了怠速稳定性。
图6是本发明实施例提供的海拔自学习修正系数计算结构示意图。上述仿真过程可以基于图6所示的结构，并在ECU中实现具体的计算过程。在该图6中，该结构包括进气管、节气门体、进气歧管以及用于检测歧管压力的歧管压力传感器，该进气歧管连接发动机。
图7是本发明实施例提供的海拔自学习修正系数算法模型仿真结果。以在海拔2500米高原为实验环境，在平原的大气压力为1013hpa，到达2500米的高原后，很快能够计算出当前的大气压力在750hpa左右，而海拔自学习修正系数为大气压力除以1013hpa。
图8是本发明实施例提供的一种海拔修正系数获取装置的结构示意图。参见图8，该装置包括：
初始化值获取模块801，用于当车辆发动机发生预设事件时，获取海拔修正系数自学习滤波器初始化值，该预设事件包括下电事件、上电事件和异常掉电事件；
使能模块802，用于根据该发动机的转速、车辆行驶速度以及指定设备的状态信息，判断车辆是否满足预设自学习使能条件；
该使能模块802还用于如果该车辆满足预设自学习使能条件，使能海拔修正系数自学习滤波器；
输入值确定模块803，用于至少根据歧管压力传感器以及步进电机的工作状态，确定海拔修正系数自学习滤波器输入值；
自学习模块804，用于根据该海拔修正系数自学习滤波器初始化值和该海拔修正系数自学习滤波器输入值，应用该海拔修正系数自学习滤波器对海拔修正系数进行自学习，得到当前海拔修正系数。
可选地，该初始化值获取模块801用于当发动机点火钥匙开关关闭，且发动机转速低于最小识别转速后，经过第一预设时长延时，确定歧管压力传感器是否故障；
如果经过延时后确定歧管压力传感器无故障，海拔修正系数自学习滤波器初始化值为歧管压力传感器值；
如果确定歧管压力传感器有故障，海拔修正系数自学习滤波器初始化值为上一次海拔修正系数自学习滤波器输出值。
可选地，该初始化值获取模块801用于当发动机点火钥匙开关开启，且发动机转速低于最小识别转速，且停机时间大于第二预设时长时，确定歧管压力传感器是否故障；
如果确定歧管压力传感器无故障，海拔修正系数自学习滤波器初始化值为歧管压力传感器值；
如果确定歧管压力传感器有故障，海拔修正系数自学习滤波器初始化值为上一次海拔修正系数自学习滤波器输出值。
可选地，该初始化值获取模块801用于当发动机异常掉电并再次恢复供电时，确定歧管压力传感器是否故障；
如果确定歧管压力传感器无故障，且发动机无转速，海拔修正系数自学习滤波器初始化值为歧管压力传感器值；
如果确定歧管压力传感器无故障，且发动机有转速，海拔修正系数自学习滤波器初始化值为1个标准大气压；
如果确定歧管压力传感器有故障，海拔修正系数自学习滤波器初始化值为1个标准大气压。
可选地，该使能模块802用于当确定同时满足发动机转速大于最小识别转速、车辆行驶速度大于预设门限值且满足以下多个第一预设条件中的任一个时，确定该车辆满足预设自学习使能条件；
其中，该多个第一预设条件包括：
歧管压力传感器或者步进电机有故障；
当前海拔修正系数小于1，且处于断油状态或者处于怠速状态但车速无故障；
节气门位置大于海拔自学习门限值，且节气门位置传感器无故障。
可选地，该输入值确定模块803用于当歧管压力传感器有故障或者步进电机有故障的时候，海拔修正系数自学习滤波器的输入值为800hpa～900hpa，优选地，海拔修正系数自学习滤波器的输入值为850hpa；
该输入值确定模块803还用于当歧管压力传感器和步进电机都无故障，且海拔修正系数小于1，且满足下列两个第二预设条件中任一项时，此时海拔修正系数自学习滤波器输入最佳选择为1000hpa～1100hpa，优选地，海拔修正系数自学习滤波器输入最佳选择为1013hpa。
其中，该两个第二预设条件包括：车辆处于断油状态；车速传感器无故障，且怠速状态标志置位，且车速大于车速门限值；
该输入值确定模块803还用于当上述任一条件都不满足的时候，海拔修正系数自学习滤波器输入值为歧管压力除以节气门前后压力比。
本发明实施例提供了一种海拔修正系数获取装置，该装置包括：
处理器；
用于存储处理器可执行指令的存储器；
其中，该处理器用于执行下述指令：
当车辆发动机发生预设事件时，获取海拔修正系数自学习滤波器初始化值，该预设事件包括下电事件、上电事件和异常掉电事件；
根据发动机的转速、车辆行驶速度以及指定设备的状态信息，判断车辆是否满足预设自学习使能条件；
如果车辆满足预设自学习使能条件，使能海拔修正系数自学习滤波器；
至少根据歧管压力传感器以及步进电机的工作状态，确定海拔修正系数自学习滤波器输入值；
根据海拔修正系数自学习滤波器初始化值和海拔修正系数自学习滤波器输入值，应用海拔修正系数自学习滤波器对海拔修正系数进行自学习，得到当前海拔修正系数。
该处理器用于执行下述指令：
当发动机点火开关关闭，且发动机转速低于最小识别转速后，经过第一预设时长延时，确定歧管压力传感器无故障是否故障；
如果经过延时后确定歧管压力传感器无故障，海拔修正系数自学习滤波器初始化值为歧管压力传感器值；
如果确定歧管压力传感器有故障，海拔修正系数自学习滤波器初始化值为上一次海拔修正系数自学习滤波器输出值。
该处理器用于执行下述指令：
当发动机点火开关开启，且发动机转速低于最小识别转速，且停机时间大于第二预设时长时，确定歧管压力传感器无故障是否故障；
如果确定歧管压力传感器无故障，海拔修正系数自学习滤波器初始化值为歧管压力传感器值；
如果确定歧管压力传感器有故障，海拔修正系数自学习滤波器初始化值为上一次海拔修正系数自学习滤波器输出值。
该处理器用于执行下述指令：
当发动机异常掉电并再次恢复供电时，确定歧管压力传感器是否故障；
如果确定歧管压力传感器无故障，且发动机无转速，海拔修正系数自学习滤波器初始化值为歧管压力传感器值；
如果确定歧管压力传感器无故障，且发动机有转速，海拔修正系数自学习 滤波器初始化值为1个标准大气压；
如果确定歧管压力传感器有故障，海拔修正系数自学习滤波器初始化值为1个标准大气压。
该处理器用于执行下述指令：
当确定同时满足发动机转速大于最小识别转速、车辆行驶速度大于预设门限值且满足以下多个第一预设条件中的任一个时，确定所述车辆满足预设自学习使能条件；
其中，所述多个第一预设条件包括：
歧管压力传感器或者步进电机有故障；
当前海拔修正系数小于1，且处于断油状态或者处于怠速状态但车速无故障；
节气门位置大于海拔自学习门限值，且节气门位置传感器无故障。
该处理器用于执行下述指令：
当歧管压力传感器有故障或者步进电机有故障的时候，海拔修正系数自学习滤波器的输入值为800hpa至900hpa；
当歧管压力传感器和步进电机都无故障，且海拔修正系数小于1，且满足下列两个第二预设条件中任一项时，海拔修正系数自学习滤波器输入值为1000hpa至1100hpa；其中，所述两个第二预设条件包括：车辆处于断油状态；车速传感器无故障，且怠速状态标志置位，且车速大于车速门限值；
当上述任一条件都不满足的时候，海拔修正系数自学习滤波器输入值为歧管压力除以节气门前后压力比。
本发明实施例提供的装置，通过在海拔修正系数自学习滤波器初始化过程中，对初始化值的获取考虑到上电自学习功能和异常掉电情况处理，优化发动机转速处理方案，并在使能过程中规避了不利用海拔自学习的条件，最终在确定海拔修正系数自学习滤波器输入时，考虑到一些设备的实际运转情况，使得对于海拔修正系数的获取，综合考虑了行车过程的实际场景，弥补了由于实际场景复杂而造成的海拔修正系数不准确的问题，提高了准确性，进而对提高了怠速稳定性。
在本发明实施例中，还提供了一种包括指令的非临时性计算机可读存储介质，例如包括指令的存储器，上述指令可由装置的处理器执行以完成上述方法。例如，该非临时性计算机可读存储介质可以是ROM、RAM(Random Access Memory,随机存取存储器)、CD-ROM(Compact Disc Read-Only Memory,光盘只读存储器)、磁带、软盘和光数据存储设备等。
一种非临时性计算机可读存储介质，当所述存储介质中的指令由装置的处理器执行时，使得装置能够执行一种海拔修正系数获取方法，所述方法包括：
当车辆发动机发生预设事件时，获取海拔修正系数自学习滤波器初始化值，该预设事件包括下电事件、上电事件和异常掉电事件；
根据发动机的转速、车辆行驶速度以及指定设备的状态信息，判断车辆是否满足预设自学习使能条件；
如果车辆满足预设自学习使能条件，使能海拔修正系数自学习滤波器；
至少根据歧管压力传感器以及步进电机的工作状态，确定海拔修正系数自学习滤波器输入值；
根据海拔修正系数自学习滤波器初始化值和海拔修正系数自学习滤波器输入值，应用海拔修正系数自学习滤波器对海拔修正系数进行自学习，得到当前海拔修正系数。
假设上述为第一种可能的实施方式，则在第一种可能的实施方式作为基础而提供的第二种可能的实施方式中，装置的存储器中，还包含用于执行以下操作的指令：
当发动机点火开关关闭，且发动机转速低于最小识别转速后，经过第一预设时长延时，确定歧管压力传感器无故障是否故障；
如果经过延时后确定歧管压力传感器无故障，海拔修正系数自学习滤波器初始化值为歧管压力传感器值；
如果确定歧管压力传感器有故障，海拔修正系数自学习滤波器初始化值为上一次海拔修正系数自学习滤波器输出值。
在第一种可能的实施方式作为基础而提供的第三种可能的实施方式中，终端的存储器中，还包含用于执行以下操作的指令：
当发动机点火开关开启，且发动机转速低于最小识别转速，且停机时间大于第二预设时长时，确定歧管压力传感器无故障是否故障；
如果确定歧管压力传感器无故障，海拔修正系数自学习滤波器初始化值为歧管压力传感器值；
如果确定歧管压力传感器有故障，海拔修正系数自学习滤波器初始化值为上一次海拔修正系数自学习滤波器输出值。
在第一种可能的实施方式作为基础而提供的第四种可能的实施方式中，终端的存储器中，还包含用于执行以下操作的指令：
当发动机异常掉电并再次恢复供电时，确定歧管压力传感器是否故障；
如果确定歧管压力传感器无故障，且发动机无转速，海拔修正系数自学习滤波器初始化值为歧管压力传感器值；
如果确定歧管压力传感器无故障，且发动机有转速，海拔修正系数自学习滤波器初始化值为1个标准大气压；
如果确定歧管压力传感器有故障，海拔修正系数自学习滤波器初始化值为1个标准大气压。
在第一种可能的实施方式作为基础而提供的第五种可能的实施方式中，终端的存储器中，还包含用于执行以下操作的指令：
当确定同时满足发动机转速大于最小识别转速、车辆行驶速度大于预设门限值且满足以下多个第一预设条件中的任一个时，确定车辆满足预设自学习使能条件；
其中，该多个第一预设条件包括：
歧管压力传感器或者步进电机有故障；
当前海拔修正系数小于1，且处于断油状态或者处于怠速状态但车速无故障；
节气门位置大于海拔自学习门限值，且节气门位置传感器无故障。
在第一种可能的实施方式作为基础而提供的第六种可能的实施方式中，终 端的存储器中，还包含用于执行以下操作的指令：
当歧管压力传感器有故障或者步进电机有故障的时候，海拔修正系数自学习滤波器的输入值为800hpa～900hpa，优选地，海拔修正系数自学习滤波器的输入值为850hpa。
当歧管压力传感器和步进电机都无故障，且海拔修正系数小于1，且满足下列两个第二预设条件中任一项时，此时海拔修正系数自学习滤波器输入最佳选择为1000hpa～1100hpa，优选地，海拔修正系数自学习滤波器输入最佳选择为1013hpa。其中，该两个第二预设条件包括：车辆处于断油状态；车速传感器无故障，且怠速状态标志置位，且车速大于车速门限值；
当上述任一条件都不满足的时候，海拔修正系数自学习滤波器输入值为歧管压力除以节气门前后压力比。
本公开实施例提供的非临时性计算机可读存储介质，通过在海拔修正系数自学习滤波器初始化过程中，对初始化值的获取考虑到上电自学习功能和异常掉电情况处理，优化发动机转速处理方案，并在使能过程中规避了不利用海拔自学习的条件，最终在确定海拔修正系数自学习滤波器输入时，考虑到一些设备的实际运转情况，使得对于海拔修正系数的获取，综合考虑了行车过程的实际场景，弥补了由于实际场景复杂而造成的海拔修正系数不准确的问题，提高了准确性，进而提高了怠速稳定性。
需要说明的是：上述实施例提供的海拔修正系数获取装置在海拔修正系数获取时，仅以上述各功能模块的划分进行举例说明，实际应用中，可以根据需要而将上述功能分配由不同的功能模块完成，即将设备的内部结构划分成不同的功能模块，以完成以上描述的全部或者部分功能。另外，上述实施例提供的海拔修正系数获取装置与海拔修正系数获取方法实施例属于同一构思，其具体实现过程详见方法实施例，这里不再赘述。
本领域普通技术人员可以理解实现上述实施例的全部或部分步骤可以通过硬件来完成，也可以通过程序来指令相关的硬件完成，所述的程序可以存储于 一种计算机可读存储介质中，上述提到的存储介质可以是只读存储器，磁盘或光盘等。
以上所述仅为本发明的较佳实施例，并不用以限制本发明，凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。

Claims (13)

  1. 一种海拔修正系数获取方法，其特征在于，所述方法包括：
    当车辆发动机发生预设事件时，获取海拔修正系数自学习滤波器初始化值，所述预设事件包括下电事件、上电事件和异常掉电事件；
    根据所述发动机的转速、车辆行驶速度以及指定设备的状态信息，判断车辆是否满足预设自学习使能条件；
    如果所述车辆满足预设自学习使能条件，使能海拔修正系数自学习滤波器；
    至少根据歧管压力传感器以及步进电机的工作状态，确定海拔修正系数自学习滤波器输入值；
    根据所述海拔修正系数自学习滤波器初始化值和所述海拔修正系数自学习滤波器输入值，应用所述海拔修正系数自学习滤波器对海拔修正系数进行自学习，得到当前海拔修正系数。
  2. 根据权利要求1所述的方法，其特征在于，当车辆发动机发生预设事件时，获取海拔修正系数自学习滤波器初始化值包括：
    当发动机点火开关关闭，且发动机转速低于最小识别转速后，经过第一预设时长延时，确定歧管压力传感器无故障是否故障；
    如果经过延时后确定歧管压力传感器无故障，海拔修正系数自学习滤波器初始化值为歧管压力传感器值；
    如果确定歧管压力传感器有故障，海拔修正系数自学习滤波器初始化值为上一次海拔修正系数自学习滤波器输出值。
  3. 根据权利要求1所述的方法，其特征在于，当车辆发动机发生预设事件时，获取海拔修正系数自学习滤波器初始化值包括：
    当发动机点火开关开启，且发动机转速低于最小识别转速，且停机时间大 于第二预设时长时，确定歧管压力传感器无故障是否故障；
    如果确定歧管压力传感器无故障，海拔修正系数自学习滤波器初始化值为歧管压力传感器值；
    如果确定歧管压力传感器有故障，海拔修正系数自学习滤波器初始化值为上一次海拔修正系数自学习滤波器输出值。
  4. 根据权利要求1所述的方法，其特征在于，当车辆发动机发生预设事件时，获取海拔修正系数自学习滤波器初始化值包括：
    当发动机异常掉电并再次恢复供电时，确定歧管压力传感器是否故障；
    如果确定歧管压力传感器无故障，且发动机无转速，海拔修正系数自学习滤波器初始化值为歧管压力传感器值；
    如果确定歧管压力传感器无故障，且发动机有转速，海拔修正系数自学习滤波器初始化值为1个标准大气压；
    如果确定歧管压力传感器有故障，海拔修正系数自学习滤波器初始化值为1个标准大气压。
  5. 根据权利要求1所述的方法，其特征在于，根据所述发动机的转速、车辆行驶速度以及指定设备的状态信息，判断车辆是否满足预设自学习使能条件包括：
    当确定同时满足发动机转速大于最小识别转速、车辆行驶速度大于预设门限值且满足以下多个第一预设条件中的任一个时，确定所述车辆满足预设自学习使能条件；
    其中，所述多个第一预设条件包括：
    歧管压力传感器或者步进电机有故障；
    当前海拔修正系数小于1，且处于断油状态或者处于怠速状态但车速无故障；
    节气门位置大于海拔自学习门限值，且节气门位置传感器无故障。
  6. 根据权利要求1所述的方法，其特征在于，至少根据歧管压力传感器以及步进电机的工作状态，确定海拔修正系数自学习滤波器输入值包括：
    当歧管压力传感器有故障或者步进电机有故障的时候，海拔修正系数自学习滤波器的输入值为800hpa至900hpa；
    当歧管压力传感器和步进电机都无故障，且海拔修正系数小于1，且满足下列两个第二预设条件中任一项时，海拔修正系数自学习滤波器输入值为1000hpa至1100hpa；其中，所述两个第二预设条件包括：车辆处于断油状态；车速传感器无故障，且怠速状态标志置位，且车速大于车速门限值；
    当上述任一条件都不满足的时候，海拔修正系数自学习滤波器输入值为歧管压力除以节气门前后压力比。
  7. 一种海拔修正系数获取装置，其特征在于，所述装置包括：
    初始化值获取模块，用于当车辆发动机发生预设事件时，获取海拔修正系数自学习滤波器初始化值，所述预设事件包括下电事件、上电事件和异常掉电事件；
    使能模块，用于根据所述发动机的转速、车辆行驶速度以及指定设备的状态信息，判断车辆是否满足预设自学习使能条件；
    所述使能模块还用于如果所述车辆满足预设自学习使能条件，使能海拔修正系数自学习滤波器；
    输入值确定模块，用于至少根据歧管压力传感器以及步进电机的工作状态，确定海拔修正系数自学习滤波器输入值；
    自学习模块，用于根据所述海拔修正系数自学习滤波器初始化值和所述海拔修正系数自学习滤波器输入值，应用所述海拔修正系数自学习滤波器对海拔修正系数进行自学习，得到当前海拔修正系数。
  8. 根据权利要求7所述的装置，其特征在于，所述初始化值获取模块用于当发动机点火开关关闭，且发动机转速低于最小识别转速后，经过第一预设时长延时，确定歧管压力传感器无故障是否故障；
    如果经过延时后确定歧管压力传感器无故障，海拔修正系数自学习滤波器初始化值为歧管压力传感器值；
    如果确定歧管压力传感器有故障，海拔修正系数自学习滤波器初始化值为上一次海拔修正系数自学习滤波器输出值。
  9. 根据权利要求7所述的装置，其特征在于，所述初始化值获取模块用于当发动机点火开关开启，且发动机转速低于最小识别转速，且停机时间大于第二预设时长时，确定歧管压力传感器无故障是否故障；
    如果确定歧管压力传感器无故障，海拔修正系数自学习滤波器初始化值为歧管压力传感器值；
    如果确定歧管压力传感器有故障，海拔修正系数自学习滤波器初始化值为上一次海拔修正系数自学习滤波器输出值。
  10. 根据权利要求7所述的装置，其特征在于，所述初始化值获取模块用于当发动机异常掉电并再次恢复供电时，确定歧管压力传感器是否故障；
    如果确定歧管压力传感器无故障，且发动机无转速，海拔修正系数自学习滤波器初始化值为歧管压力传感器值；
    如果确定歧管压力传感器无故障，且发动机有转速，海拔修正系数自学习滤波器初始化值为1个标准大气压；
    如果确定歧管压力传感器有故障，海拔修正系数自学习滤波器初始化值为1个标准大气压。
  11. 根据权利要求7所述的装置，其特征在于，所述使能模块用于当确定 同时满足发动机转速大于最小识别转速、车辆行驶速度大于预设门限值且满足以下多个第一预设条件中的任一个时，确定所述车辆满足预设自学习使能条件；
    其中，所述多个第一预设条件包括：
    歧管压力传感器或者步进电机有故障；
    当前海拔修正系数小于1，且处于断油状态或者处于怠速状态但车速无故障；
    节气门位置大于海拔自学习门限值，且节气门位置传感器无故障。
  12. 根据权利要求7所述的装置，其特征在于，所述输入值确定模块用于当歧管压力传感器有故障或者步进电机有故障的时候，海拔修正系数自学习滤波器的输入值为800hpa至900hpa；
    所述输入值确定模块还用于当歧管压力传感器和步进电机都无故障，且海拔修正系数小于1，且满足下列两个第二预设条件中任一项时，海拔修正系数自学习滤波器输入值为1000hpa至1100hpa；其中，所述两个第二预设条件包括：车辆处于断油状态；车速传感器无故障，且怠速状态标志置位，且车速大于车速门限值；
    所述输入值确定模块还用于当上述任一条件都不满足的时候，海拔修正系数自学习滤波器输入值为歧管压力除以节气门前后压力比。
  13. 一种海拔修正系数获取装置，其特征在于，所述装置包括：
    处理器；
    用于存储处理器可执行指令的存储器；
    其中，所述处理器被配置为：
    当车辆发动机发生预设事件时，获取海拔修正系数自学习滤波器初始化值，所述预设事件包括下电事件、上电事件和异常掉电事件；
    根据所述发动机的转速、车辆行驶速度以及指定设备的状态信息，判断车辆是否满足预设自学习使能条件；
    如果所述车辆满足预设自学习使能条件，使能海拔修正系数自学习滤波器；
    至少根据歧管压力传感器以及步进电机的工作状态，确定海拔修正系数自学习滤波器输入值；
    根据所述海拔修正系数自学习滤波器初始化值和所述海拔修正系数自学习滤波器输入值，应用所述海拔修正系数自学习滤波器对海拔修正系数进行自学习，得到当前海拔修正系数。
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CN103241099A (zh) * 2013-05-23 2013-08-14 奇瑞汽车股份有限公司 空调控制的方法及装置
CN103644036A (zh) * 2013-11-19 2014-03-19 东风康明斯发动机有限公司 发动机高原动力性能控制方法
CN103711600A (zh) * 2013-12-23 2014-04-09 奇瑞汽车股份有限公司 海拔修正系数获取方法和装置

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CN103711600B (zh) 2016-05-18
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RU2016125554A (ru) 2018-01-30
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