Abstract:
A method of diagnosing a vehicle compressed-air generating system, the method including the steps of: acquiring a number of operating data items associated with operation of the compressed-air generating system between turn-on of the system and subsequent turn-off of the system; processing the acquired operating data items and accumulating the data items to create at least one database; and examining the location of the data items in the database to determine malfunction and/or potential malfunction situations of the compressed-air generating system.

Description:
BACKGROUND OF THE INVENTION  
         [0001]    1. Field of the Invention  
           [0002]    The present invention relates to a method of diagnosing a vehicle compressed-air generating system.  
           [0003]    2. Description of the Related Art  
           [0004]    Compressed-air generating systems are known in which a compressor, driven by an electric motor or combustion engine, supplies compressed air to a tank where it is stored for use by a number of on-vehicle pneumatic systems, e.g. air-powered suspensions, vehicle component pneumatic actuators, etc.  
           [0005]    As is also known, ageing and wear of the compressor and/or members governing air flow and/or storage and/or use are responsible for a noticeable fall in the efficiency of the system.  
           [0006]    A demand therefore exists for a method capable of fully automatically determining malfunctioning of the system, and which also provides for determining gradual deterioration of the system so as to predict pending malfunction of the system well in advance.  
         BRIEF SUMMARY OF THE INVENTION  
         [0007]    According to the present invention, there is provided a method of diagnosing a vehicle compressed-air generating system, characterized by comprising the steps of: acquiring a number of operating data items associated with operation of the compressed-air generating system between turn-on of the system and subsequent turn-off of the system; processing the acquired operating data items and accumulating the data items to create at least one database; and examining the location of the data items in said database to determine malfunction and/or potential malfunction situations of said compressed-air generating system. 
       
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0008]    A preferred, non-limiting embodiment of the invention will be described by way of example with reference to the accompanying drawings, in which:  
         [0009]    [0009]FIG. 1 shows an operating flow chart of the method according to the present invention;  
         [0010]    [0010]FIG. 2 shows a first database used in the method according to the present invention;  
         [0011]    [0011]FIG. 3 shows a variation of the method according to the present invention;  
         [0012]    [0012]FIG. 4 shows a second database used in the method according to the present invention. 
     
    
     DETAILED DESCRIPTION OF THE INVENTION  
       [0013]    [0013]FIG. 1 shows the operations performed in accordance with a first embodiment of the method according to the present invention for diagnosing the compressed-air generating system of a vehicle, in particular an industrial vehicle (e.g. a bus).  
         [0014]    To begin with, a block  100  determines whether the compressed-air generating system is turned on. If it is not (system off), block  100  remains on standby; conversely (system on), block  100  goes on to a block  110 .  
         [0015]    Block  110  acquires and memorizes the following quantities:  
         [0016]    the speed ω comp  of the compressed-air generating system compressor;  
         [0017]    the compressed-air temperature T air ;  
         [0018]    a temperature associated with operation of the compressor, in particular the temperature T water  of the compressor cooling fluid (water) or the temperature of the compressor body.  
         [0019]    Block  110  is followed by a block  120 , which calculates the temperature difference AT between the compressed-air temperature T air  and compressor cooling fluid (water) temperature T water , i.e.:  
         Δ T=T   air   −T   water    
         [0020]    Block  120  is followed by a block  125 , which forms a data structure in which operating states S(ΔT, ω comp ) of the compressed-air generating system are determined and stored as a function of the calculated ΔT value and compressor speed ω comp . They can be stored in any acceptable memory, or memorized by some other technique.  
         [0021]    The data structure also memorizes the time lapse Ts the compressed-air generating system remains in each operating state S(ΔT, ω comp ).  
         [0022]    For example, the database can be represented in the form of a Cartesian X-Y spot diagram—FIG. 2—in which each spot corresponds to an operating state; and the diameter of the spot shows how long the operating state is recorded, i.e. how long the compressed-air generating system remains in that particular operating state.  
         [0023]    Block  125  is followed by a block  130 , which determines whether the compressed-air generating system has been turned off. If it has not (system on and running), block  130  goes back to block  110 ; conversely (system off and blocked), block  130  goes on to a diagnosis block  170 .  
         [0024]    On exiting block  130 , the total trip time Ttrip (measured in seconds, minutes or hours) between turn-on and turn-off of the compressed-air generating system is also calculated (block  140  between blocks  130  and  170 ), and equals the sum of the time lapses in the various recorded operating states.  
         [0025]    The operating states are thus memorized and accumulated in different operating condition bands (shown by a grid in FIG. 2).  
         [0026]    Alternatively or in addition, as opposed to the time lapse in each operating state, the percentage of total trip time Ttrip spent in that particular operating state may be memorized.  
         [0027]    When the compressed-air generating system is turned off, the three-dimensional data structure thus contains the time lapses in the various recorded operating states.  
         [0028]    Repeated system trips generate a database containing all the states in which the system has operated.  
         [0029]    According to the present invention, block  170  periodically checks the database containing all the accumulated data structures to determine any malfunction situations.  
         [0030]    For which purpose, the X-Y diagram map (FIG. 2) shows various calibratable regions, including:  
         [0031]    an alarm region Z 1 ;  
         [0032]    a prealarm region Z 2 ; and  
         [0033]    a normal or safe operating region Z 3 .  
         [0034]    Regions Z 1 , Z 2  and Z 3  in the X-Y diagram can be calibrated as a function of the characteristics of the compressed-air generating system.  
         [0035]    The check by block  170  may be performed in three ways:  
         [0036]    by checking the data structure at the end of each operating cycle of the compressed-air generating system to determine instantaneous malfunctions (e.g. location of at least one operating state in alarm region Z 1 );  
         [0037]    by checking the data structures of a number of operating cycles of the same system to determine gradual deterioration (e.g. migration of accumulated operating states from normal operating region Z 3  to regions Z 1  and Z 2 ;  
         [0038]    by comparing the data structures of different compressed-air generating systems to determine anomalies in one system with respect to others acting as a reference.  
         [0039]    Defective operation of the system can be established on the basis of various criteria, including:  
         [0040]    an operating state time lapse in alarm region Z 1  over and above a given maximum value;  
         [0041]    migration of operating state time lapses towards alarm region Z 1 ;  
         [0042]    the operating state pattern of one system differs from that of a number of other systems.  
         [0043]    In the alternative method shown in FIG. 3, a block  200  determines whether the compressed-air generating system is turned on. If it is not (system off), block  200  remains on standby; conversely (system on), block  200  goes on to a block  210 .  
         [0044]    Block  210  determines whether the pressure P air  of the compressed air generated by the system is above a threshold pressure value S1, i.e.:  
         P air &gt;S1  
         [0045]    If it is not (P air &lt;S1), block  210  goes back to block  200 ; conversely (P air &gt;S1), block  210  goes on to a block  220 .  
         [0046]    In other words, the system remains in the block  200 - 210  loop until the pressure of the compressed air generated by the system increases sufficiently to reach threshold value S1.  
         [0047]    Block  220  determines the time pattern of pressure P air , which, as is known, has a substantially alternating sinusoidal time pattern in which pressure peaks alternate with lower-pressure regions (dips).  
         [0048]    More specifically, block  220  determines when the recorded pressure P air  exceeds a second threshold value S2 and falls below a third threshold value S3 preferably lower than second threshold value S2.  
         [0049]    Block  220  is followed by a block  230 , which determines whether the compressed-air generating system has been turned off. If it has not (system on), block  230  goes back to block  220 ; conversely (system off), block  230  is followed by a block  240 , which determines the time Ttrip between turn-on (block  200 ) and turn-off (block  230 ) of the system, i.e. the time Ttrip the compressed-air generating system has been on continuously, thus performing a complete operating cycle.  
         [0050]    Block  240  is followed by a block  250 , which calculates the frequency F S2  of pressure values above threshold S2, i.e. determines the relationship between the number of occurrences in which pressure P air  exceeds threshold S2, and the time Ttrip the compressed-air generating system has been on continuously.  
         [0051]    Block  250  also calculates the frequency F S3  of pressure values below threshold S3, i.e. determines the relationship between the number of occurrences in which pressure P air  is below threshold S 3 , and the time Ttrip the compressed-air generating system has been on continuously.  
         [0052]    Block  250  is followed by a block  260 , which, for each operating cycle examined, stores in the respective frequency F S2  value of the pressure values above threshold S2.  
         [0053]    A first two-dimensional database is thus formed (FIG. 4), which can be represented in the form of a Cartesian diagram, the X axis of which shows successive operating cycles, and the Y axis the F S2  frequency values associated with each cycle.  
         [0054]    Block  260  also stores, for each operating cycle examined, the respective frequency F S3  value of the pressure values below threshold S3.  
         [0055]    A second two-dimensional database is thus formed, which can be represented in the form of a Cartesian diagram, the X axis of which shows successive operating cycles, and the Y axis the F S3  frequency values associated with each cycle.  
         [0056]    According to the present invention, a process independent of the operations performed in blocks  200 - 260 , and indicated by a block  270  in FIG. 3, periodically checks one or both databases to determine any malfunction situations.  
         [0057]    Defective operation of the compressed-air generating system can be established on the basis of various criteria, including:  
         [0058]    F S2  and F S3  frequency values above upper prealarm and alarm values;  
         [0059]    F S2  and F S3  frequency values below lower prealarm and alarm values;  
         [0060]    migration of F S2  and F S3  frequency values towards prealarm and alarm values.  
         [0061]    The prealarm and alarm values are calibratable.  
         [0062]    The method according to the present invention therefore provides for fully automatically determining a malfunction situation of the compressed-air generating system.