Abstract:
A system and method for measuring engine oil quality is disclosed. The system and method include: a plurality of sensors detecting oil quality data; and a processor in communication with the plurality of sensors to receive the oil quality data and adapted to execute a transfer function to output qualitative and quantitative measurements with respect to contamination of the oil based upon the oil quality data.

Description:
FIELD OF THE INVENTION 
       [0001]    The present invention relates generally to systems, devices and methods for analyzing fluids and more specifically to systems, devices and methods for analyzing engine oil. 
       BACKGROUND 
       [0002]    As is well-known, oil is used as a lubricant for mechanical (particularly metallic) machines. More specifically, oil is widely used as a lubricant for engines used in cars, trucks and other vehicles. 
         [0003]    Unfortunately, engine oil can become contaminated with a variety of pollutants including fuel, biodiesel, water and soot. These pollutants can severely undermine the performance characteristics of the fluid and lead to catastrophic engine failure. This is particularly problematic for the owners and operators of fleets of vehicles. 
         [0004]    Two approaches are generally used in the art to address this problem. One approach involves the periodic replacement of engine oil based on duration of use or mileage considerations. However, this approach lacks in accuracy. Consequently, the oil may be replaced well beyond the ideal replacement period leading to substandard performance and engine degradation. On the other hand, the premature replacement of oil can be costly and wasteful with respect to oil use per se. 
         [0005]    In short, the conventional systems and methods prior art does not appear to teach how to distinguish multiple contamination types from each other or how to quantify the levels of such contaminants. Accordingly, a need remains for a more accurate and effective system and method for assessing engine oil quality. Specifically, a need remains for a system or method for identifying and distinguishing the nature and level of multiple contamination types in motor oil and other fluids. 
       SUMMARY 
       [0006]    The need in the art is addressed by the system and method for measuring engine oil quality of the present invention. A system for measuring engine oil quality comprises a plurality of sensors detecting oil quality data; and a processor in communication with the plurality of sensors to receive the oil quality data and adapted to execute a transfer function to output qualitative and quantitative measurements with respect to contamination of the oil based upon the oil quality data. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0007]      FIG. 1  is a block diagram of an illustrative embodiment of a system in accordance with the present invention. 
           [0008]      FIG. 2  is a process flow map illustrating the method of the illustrative embodiment of the present invention. 
           [0009]      FIG. 3  is a flow diagram showing an illustrative embodiment of the transfer function of the method of the present invention. 
       
    
    
     DETAILED DESCRIPTION 
       [0010]    The present invention relates generally to systems, devices and methods for analyzing fluids and more specifically to systems, devices and methods for analyzing engine oil. 
         [0011]    The following description is presented to enable one of ordinary skill in the art to make and use the invention and is provided in the context of a patent application and its requirements. Various modifications to the preferred embodiments and the generic principles and features described herein will be readily apparent to those skilled in the art. Thus, the present invention is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features described herein. 
         [0012]      FIG. 1  is a block diagram of an illustrative embodiment of a system in accordance with the present invention. As shown in the Figure, the system  10  includes a temperature sensor  12 , a density sensor  14 , a dielectric constant sensor  16  and a viscosity sensor  18  mounted in a host vehicle or machine (not shown). In the illustrative embodiment, the sensors are implemented with a model FPS2800 sensor assembly  20  manufactured and sold by Measurement Specialty Inc. This assembly is adapted to measure temperature, density, viscosity and dielectric constant. 
         [0013]    These data are provided to a microprocessor  30  adapted to execute a program or a lookup table stored in a tangible memory medium  40  to output qualitative measures with respect to at least four major oil contaminants including, in the illustrative embodiment, diesel fuel, biodiesel, water and soot. 
         [0014]    Embodiments described herein can take the form of an entirely hardware implementation, an entirely software implementation, or an implementation containing both hardware and software elements. Embodiments may be implemented in software, which includes, but is not limited to, application software, firmware, resident software, microcode, etc. 
         [0015]    The steps described herein may be implemented using any suitable controller or processor, and software application, which may be stored on any suitable storage location or computer-readable medium. The software application provides instructions that enable the processor to cause the receiver to perform the functions described herein. 
         [0016]    Furthermore, embodiments may take the form of a computer program product accessible from a computer-usable or computer-readable medium providing program code for use by or in connection with a computer or any instruction execution system. For the purposes of this description, a computer-usable or computer-readable medium can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. 
         [0017]    The medium may be an electronic, magnetic, optical, electromagnetic, infrared, semiconductor system (or apparatus or device), or a propagation medium. Examples of a computer-readable medium include a semiconductor or solid state memory, magnetic tape, a removable computer diskette, a random access memory (RAM), a read-only memory (ROM), a rigid magnetic disk, and an optical disk. Current examples of optical disks include DVD, compact disk-read-only memory (CD-ROM), and compact disk-read/write (CD-RAN). 
         [0018]    The output from the microprocessor  30  can provide in high, medium and low classification levels that can provide a tiered alert on oil quality in terms of healthy, warning and condemning and also provide relative levels of these contaminants, which can point to specific engine problems and provide a guideline for maintenance. The microprocessor  30  may be included in an electronic control unit  50  or engine control module. 
         [0019]      FIG. 2  is a process flow map illustrating the method of the illustrative embodiment of the system depicted in  FIG. 1 . As shown in  FIG. 2 , fresh oil  110  is contaminated with fuel, coolant, water and soot  120  resulting in contaminated oil  130 . A host vehicle&#39;s engine provides heating, cooling and/or agitation as represented by the heating element  140 . The sensor assembly  20  is coupled to the resulting heated, cooled, agitated contaminated oil and outputs a viscosity, density, dielectric constant and temperature data set  160 . This data  160  are fed to a transfer function  180  along with the historical data  170  as initial value assigned to the parameters to be predicted, implemented via an algorithm discussed more fully below in software with coefficients stored in memory  40  and executed by the processor  30  in the illustrative embodiment of  FIG. 1 . As depicted in  FIG. 2 , the transfer function  180  provides predictions  190  of oil quality with respect to levels of fuel, soot and water contamination. 
         [0020]      FIG. 3  is a flow diagram showing an illustrative embodiment of the transfer function  180  of the method of the present invention. An average sensor reading is compared with a historical database, via step  200 . A determination is made on whether there is a large difference between the sensor reading and the historical database, via step  202 . 
         [0021]    If there is a large difference between the sensor reading and the historical database, a determination is then made on whether it is an oil type change or oil sensor malfunction, via step  204 . If it is an oil type change or oil sensor malfunction, then oil type check and a sensor check are flagged to the driver, via step  206 . If it is not an oil type change or oil sensor malfunction, then sudden oil quality change, such as significant foreign matter incursion into the oil system, is flagged to the driver, via step  208 . 
         [0022]    If there is not a large difference between the sensor reading and the historical database, the reading is fed into a transfer function, via step  210 . Next, the last oil quality data in historical data base is used as initial value to run an iteration for oil quality at this moment, via step  212 . The initial value is then fed back to historical database with a time tracker, via step  214 . 
         [0023]    In the illustrative embodiment, the coefficients shown in Table I below are used in equations [1-3] below to solve for and thereby predict the levels of fuel, soot and water contamination as three variables using Microsoft&#39;s Excel Solver addin, MATLAB or other equation solving utility known in the art: 
         [0000]    
       
         
               
               
               
               
               
             
               
               
               
               
               
             
           
               
                   
                 TABLE I 
               
               
                   
                   
               
               
                   
                   
                 V 
                 D 
                 DC 
               
               
                   
                 Predictor 
                 Coef 
                 Coef 
                 Coef 
               
               
                   
                   
               
             
             
               
                   
               
             
          
           
               
                   
                 Constant 
                 127.071 
                 0.777159 
                 2.23742 
               
               
                   
                 F 
                 −2.3058 
                 0.002771 
                 0.013012 
               
               
                   
                 B 
                 −11.9329 
                 0.016678 
                 −0.16412 
               
               
                   
                 S 
                 6.07014 
                 −0.00691  
                 0.010789 
               
               
                   
                 W 
                 −17.2428 
                 0.071881 
                 1.0516 
               
               
                   
                 T 
                 −2.30702 
                 0.001473 
                 −0.00333 
               
               
                   
                 F*B 
                 −3.69148 
                 0.003506 
                 −0.01087 
               
               
                   
                 F*S 
                 −0.04001 
                 0.000205 
                 0.00854 
               
               
                   
                 F*W 
                 0.41118 
                 −0.00059  
                 −0.01576 
               
               
                   
                 B*S 
                 −1.9884 
                 0.002849 
                 −0.06978 
               
               
                   
                 B*W 
                 −49.046 
                 0.040535 
                 2.3904 
               
               
                   
                 S*W 
                 0.3253 
                 −0.00486  
                 −0.03358 
               
               
                   
                 F*B*S 
                 0.22608 
                 1.44E−06 
                 0.005393 
               
               
                   
                 F*B*W 
                 15.2405 
                 −0.03727  
                 −0.21337 
               
               
                   
                 B*S*W 
                 12.3516 
                 −0.01166  
                 −0.4639 
               
               
                   
                 F*B*S*W 
                 −3.25558 
                 0.007752 
                 0.020259 
               
               
                   
                 F 2   
                 −0.01102 
                 −4.6E−05 
                 −0.00381 
               
               
                   
                 B 2   
                 16.4294 
                 −0.01969  
                 0.1263 
               
               
                   
                 S 2   
                 −0.05204 
                 −1.9E−05 
                 0.024844 
               
               
                   
                 W 2   
                 7.0826 
                 −0.03783  
                 −1.14263 
               
               
                   
                 T 2   
                 0.011673 
                 −1.3E−05 
                 1.86E−05 
               
               
                   
                 F*T 
                 0.023582 
                 −2.8E−05 
                 0.000174 
               
               
                   
                 S*T 
                 −0.05236 
                 0.00014  
                 0.00059 
               
               
                   
                 B*T 
                 0.070726 
                 −0.00015  
                 −0.00082 
               
               
                   
                 W*T 
                 0.115131 
                 −0.00035  
                 0.007059 
               
               
                   
                 F*S*T 
                 0.000252 
                 −2.7E−06 
                 −8.5E−05 
               
               
                   
                 F*B*T 
                 −0.00658 
                  2.4E−05 
                 9.39E−05 
               
               
                   
                 F*W*T 
                 −0.00429 
                 1.26E−05 
                 0.000424 
               
               
                   
                 F*B*S*T 
                 −0.00116 
                     −2E−06 
                 −2.6E−05 
               
               
                   
                 F*B*W*T 
                 0.000559 
                 0.000025 
                 0.003595 
               
               
                   
                 B*S*W*T 
                 −0.06301 
                 −3.6E−05 
                 0.005109 
               
               
                   
                 B*S*T 
                 0.026375 
                     −5E−05 
                 −0.00067 
               
               
                   
                 B*W*T 
                 0.13419 
                 0.000362 
                 −0.03207 
               
               
                   
                 S*W*T 
                 −0.00456 
                 7.31E−05 
                 −0.00135 
               
               
                   
                   
               
             
          
         
       
     
         [0024]    where F is fuel, B is biodiesel, S is soot, W is water and T is temperature. 
         [0025]    Hence, 
         [0000]      Viscosity=127.071+(−2.3058)× F +(−11.9329)× B+ 6.07014 ×S +(−17.2428) × W+ (−2.30702)× T +(−3.69148)× F×B+ (−0.04001)× F×S+ 0.41118 ×F×W+ (−1.98884)× B×S+ (−49.046)× B×W+ (0.3253)× S×W+ (0.22608)× F×B×S+ (15.2405) × F×B×W+ (12.3516)× B×S×W +(−3.25558)× F×B×S×W+ (−0.01102)× F{circumflex over ( 0 )} 2+(16.4294)× B{circumflex over ( 0 )} 2+(−0.05204)× S{circumflex over ( 0 )} 2+(7.0826)× W{circumflex over ( 0 )} 2+(0.011673)× T{circumflex over ( 0 )} 2+(0.023582)× F×T +(−0.05236)× S×T+ (0.070726)× B×T+ (0.115131)× W×T +(0.000252)× F×S×T+ (−0.00658)× F×B×T+ (−0.00429) × F×W×T +(−0.00116)× F×B×S×T+ (0.000559)× F×B×W×T+ (−0.06301) XB×S×W×T +(0.026375)× B×S×T+ (0.13419)× B×W×T+ (−0.00456)× S×W×T   [Equation 1]
 
         [0000]      Density=0.777159+(0.002771)× F+ (0.016678)× B +(−0.00691)× S+ (0.071881)× W +(0.001473)× T+ (0.003506)× F×B+ (0.000205)× F&#39;S +(−0.00059)× F×W+ (0.002849)× B×S +(0.040535)× B×W+ (−0.00486)× S×W+ (1.44 E− 06)× F×B×S+ (−0.03727)× F×B×W +(−0.01166)× B×S×W +(0.007752)× F×B×S×W +(−4.6 E −05)× F ̂2+(−0.01969)× B̂ 2+(−1.9 E− 05) × Ŝ 2+(0.03783)× Ŵ 2+(−1.3 E− 05) × T̂ 2+(−2.8 E− 05)× F×T +(0.00014)× S×T ++(−0.00015) × B×T +(−0.00035)× W×T+ (−2.7 E− 06)× F×S×T +(2.4 E− 05)× F×B×T+ (1.26 E− 05)× F×W×T +(−2 E− 06)× F×B×S×T+ (0.000025)× F×B×W×T+ (−3.6 E− 05) XB×S×W×T+ (−5 E− 05)× B×S×T+ (0.000362)× B×W×T+ (7.31 E− 05) × S×W×T   [Equation 2]
 
         [0000]      Dielectric constant=2.23742+(0.013012)× F +(−0.16412)× B+ (0.010789)× S +(1.0516)× W +(−0.00333)× T +(−0.01087)× F×B +(0.00854)× F×S+ (−0.01576 F×W+ (−0.06978)× B×S+ (2.3904)× B×W+ (−0.03358)× S×W +(0.005393) × F×B×S+ (−0.21337)× F×B×W +(−0.4639)× B×S×W+ (0.020259) × F×B×S×W+ (−0.00381)× F̂ 2+(0.1263) × B̂ 2+(0.024844)×Ŝ2+(−1.14263) × Ŵ 2+(1.86 E− 05)× T̂ 2+(0.000174)× F×T+ (0.00059)× S×T ++(−0.00082)× B×T+ (.--7059)× W×T +(−8.5 E− 05)× F×S×T+ (9.29 E− 05)× F×B×T +(0.000424)× F×W×T +(−2.6 E− 05)× F×B×S×T+ (0.003595)× F×B×W×T+ (0.005109) XB×B×S×W×T +(−0.00067)× B×S×T+ (−0.03207)× B×W×T+ (−0.00135)× S×W×T   [Equation 3]
 
         [0026]    As stated above, the coefficients shown in Table I above are used in equations [1-3] above to solve for and thereby predict the levels of fuel, soot and water contamination in the oil. The resulting values of step  214  are then compared to a plurality of reference tables (in this embodiment there are three reference tables one for water contamination, one for fuel contamination and one for soot contamination, where each comparison has a high threshold value A and a low threshold value B), via step  216 . Oil quality is classified into three categories (high, medium and low) based upon these comparisons, via step  218 . Finally, for each type of contamination, a red indication is flagged if the contamination is high, a yellow indication is flagged if the contamination is medium, and a green indication is flagged if the contamination is low, via step  220 . 
         [0027]    Accordingly, a system and method in accordance with an embodiment provides a more accurate and effective system and method for assessing engine oil quality on a real time basis. Specifically, the invention provides a system or method for identifying and distinguishing the nature and level of multiple contamination types in motor oil and other fluids. 
         [0028]    Although the present invention has been described in accordance with the embodiments shown, one of ordinary skill in the art will readily recognize that there could be variations to the embodiments and those variations would be within the spirit and scope of the present invention. Accordingly, many modifications may be made by one of ordinary skill in the art without departing from the spirit and scope of the present invention.