Engine Oil Quality Deterioration Estimation Using Integrated Sensory System

Engine oil deterioration level affects working and performance of internal combustion engine. Hence, it is necessary to compare the deterioration level of engine oils, with focus on kinematic viscosity, oxidation, nitration etc. which are important oil testing parameters. If without quantifying the remaining useful life of the engine oil, it is changed too early, results in insu�cient use of already depleting resources and also unwanted impact on environment while disposing. Changing the engine oil too late with deteriorated quality, will hamper the performance of engine. To determine optimum point for changing engine oil, in present study oil testing is carried out for vehicle which is due for servicing. The oil samples collected randomly from vehicles which came to an authorized service station for servicing covering a large range from the �rst servicing to the �fth servicing were tested. Oil samples were �rst tested by a viscometer and FTIR spectroscopy in a laboratory as per standard. The samples were then tested on a setup of sensors designed and developed by the authors. The results provided a fairly strong positive relationship between important engine oil deterioration parameters such as kinematic viscosity, oxidation and nitration with the determination coe�cient R 2 = 0.97.Out of total collected samples about 8% samples were within usable limit. The study uncovers different oil deterioration sensor methods which provide low cost, on-site handy solutions for oil condition monitoring and the forecasting of the remaining useful life of the engine oil.


Introduction
Internal combustion engine operations and output are affected by engine oil, different operating conditions that affect the acceleration of oil degradation .Various parameters de ne the safe level of operation for engine oil. Above this safe level it will affect the working and performance of the engine (Kobayashi and Kondoh, 2020). The engine oil itself is a complex hydrocarbon compound (Agocs et al., 2020). Along with the aging process of the engine oil some contaminations are also added during the service period of engine oil such as wear debris, glycol, soot, water, etc.
(Shinde and Bewoor, 2020a).Based on above facts the determination and quanti cation of engine oil deterioration is really complex because, it is also dependent on the driving conditions (Schwartz and Mettrick, 2010)and the engine type (Bennett et al., 2010). As per guidelines provided by the vehicle manufacturers there are recommendations for engine oil change cycle. But these recommendations are based on standard driving conditions. Considering that the travelling distance of vehicles is much less than a particular kilometre range (if proper driving conditions are followed) then there are chances that such engine oil may not be deteriorated. It is a known fact that most of the crude oil required in India for manufacturing engine oil is imported, so there is a need for quanti cation of the deteriorated engine oil before replacement during a regular servicing schedule. Secondly monitoring of engine oil deterioration will provide important information about possibility of engine failure (Lu et al., 2021). To quantify engine oil deterioration level various laboratory methods are available depending on parameters, such as: viscosity, nitration, oxidation, sulfonation, TAN, TBN, water and glycol content, or determination of antioxidant content (Gołębiowski et al., 2018). This provides the actual oil deterioration level, but most of these methods are destructive. Also, the costs associated with these methods are higher as compared to the cost involved in changing the engine oil (light-duty vehicles).
There can be o ine condition monitoring or online condition monitoring of engine oil under use. For large stationary engines de nitely an online condition monitoring method is required. It is obvious that the cost of the online condition monitoring method is higher than the o ine condition monitoring method. In some light duty vehicles the engine oil condition is determined approximately by some of the vehicle parameters such as the temperature of the engine, the duration of travel, the speed of the vehicle, etc., (Wei et al., 2019). There are some disadvantages of the off-line laboratory analysis. Oil samples must be properly collected over speci c intervals. Sample testing will be costlier because of precision laboratory equipment cost. This will consume more time in testing. Also, it involves sample handling time from vehicle to testing facility. This leads to need of additional time to sample and analyse the results.
Infrared analysis (IR) is a powerful tool for analysis of degradation of engine oil (Shinde and Bewoor, 2020b)- . Parameters such as oxidation, nitration, etc., along with contaminants such as fuel, glycol (Abdulmunem et al., 2020), soot, sulphate by-products, anti-wear components, etc., can be traced using the IR absorption spectrum (Agoston et al., 2008)- (Kral et al., 2014) or atomic force microscopy (Kampet al., 2014). Oxidation index is the primary parameters that is examined by FT-IR spectroscopy in the process of used oil analysis (van de Voort et al., 2006). Similarly, oxidation level of deteriorated engine oil can be predicted by the UV-Vis micro-volume spectrometer instrument (Holland et al., 2021). Also, various latest handy instruments developed for degradation analysis . The viscosity of the oil can physically increase because of oxidation (Maleville et al., 2006). All covalent chemical bonds in organic molecules absorb IR radiation at a characteristic wavelength, based on the type of antioxidants in the material, anti-wear components, hydroxyl, carbonyl compounds, sulfonate detergents, etc. According Previous research showed the possibility of using colour features to analyse particles for automated wear debris classi cation (Myshkin et al., 2001).Published literature shows use of an optical colour sensor with a blue LED as a light source and LDR or colour scale as per the ASTM D1500 standard for colour analysis (Suhanto et al., 2021). That displays a strong correlation to a change in voltage across LDR with the pH value and the viscosity of the oil (Kumar et al., 2005).The RGB sensor output in three wavelengths viz. red, green and blue demonstrate a good correlation to viscosity, TAN and Fe-particle concentration(C. V. Ossia et al., 2010).Utilizing Polychromatic (white LED) source and colour sensor shows that the output coordinates go up with an increase in the oil degradation. Arti cially degraded oils, output results are also compared with viscometer, TAN and UV-VIS photo spectrometry (Ossia and Kong, 2012).Previous studies have emphasized use of a colour sensor to measure the deterioration in the TAN.The TAN and oxidation parameters increase results in darkening the colour of the oil (Myshkin and Markova, 2018).An object shape based optical sensing technique used for analysing lubricants that are contaminated can distinguish 1%, 4%, 7%, and 10% water contamination, coolant, and gasoline (Bordatchev et al., 2014). Also, a study of change in colour measurement for the L* a* b* system by colorimeter -spectrophotometer CM-3500 shows a negative correlation between kilometres travelled (Wolak, 2016). An opto-resistive quasi-digital sensor demonstrates measurement technique to quantify deterioration level (Sanga et al., 2018). Glass-based thick lm sensors working on samples that were degraded arti cially show decisively that they can be worked under high temperature up to 120°C and the sensor response time can be reduced greatly because of the metal particles that are in the oil (Yang et al., 2019).Quartz tuning forks and extensional micro resonators are used to demonstrate the measurements for viscosity and density (Toledo et al., 2014). Higher order model analysis is advantageous in the viscosity and density calculation from measured resonance parameters(Voglhuber-Brunnmaier and Jakoby, 2020).A shear horizontal surface acoustic wave (SH-SAW) sensor can trace the electric and mechanical properties of the engine oil (Kobayashi and Kondoh, 2020).KV 0 measurement by rotary viscometer shows that temperature has similar nonlinear characteristics for both used and unused oils (Landowski and Baran, 2019 Research undertaken in this intent to ll the research gap, experimental study is reported in this paper. Experimentation is carried out of randomly collected eld samples (more than 700) of engine oil from different vehicles over wide range of distance covered. The primary goal of this study was to come up with a low-cost integrated sensors setup, to quantify engine oil deterioration by comparing the results obtained from multiple sensors. Developed set up comprises of sensor array of low cost viz. are low-cost IR sensor setup, uid property sensor (FPS) and colour sensor. Literature review reviled, no prior studies have considered an integrated sensors approach for quanti cation of engine oil quality deterioration with above mentioned sensors. The evaluation was carried out on the basis of modi cations in selected physicochemical characteristics of engine oils that take place during actual operation. Study related to such changes in physicochemical properties of selected engine oil parameter viz. degree of oxidation, KV and the degree of nitration, are presented in the results and discussion section. The organization of the remainder of the paper is as follows: Section 2 discusses methods used to measure deterioration in the three major parameters. Section 3 describes in detail the integrated sensor setup designed by the author. Section 4 highlights the results and the ensuing discussion. Section 5 contains the conclusion of the paper.

Materials And Methods
To prove the feasibility of the integrated sensors setup used for measuring deterioration in the oil in terms of oxidation, KV and nitration, samples of oil were gathered at random intervals from cars just after they had an oil change. SAE class5W30 engine oil samples were gathered from an authorized service station operating in the city of Pune, India.
With the main aim to identify the effect of deterioration in the engine oil, the following parameters are investigated in this research work: Kinematic viscosity (ASTM D7042 similar to ASTM D445) measured with a laboratory equipment viscometer (Make: Stabinger Viscometer model: 'SVM 3000').
Experimental procedure for the measurement of oxidation and nitration on FT-IR spectroscopy standard lab equipment is discussed in detail and can be referred to in earlier publications (Shinde and Bewoor, 2020a).For measurement of KV 0 ,a SVM 3000 Stabinger Viscometer which is a rotational viscometer with cylinder geometry is utilized. The authors studied the brochure and the procedure to use this instrument from the OEM. It depends on a modi ed Couette principle with an outer tube that rotates rapidly and an inner measuring bob which rotates at a slower rate. The measurement principle relies on a torque and on speed measurement.
A rotating magnet in the SVM 3000 produces an eddy current eld with an exact speed dependent brake torque. This equipment measures KV, dynamic viscosity (0.2 to 20 mPa.s), density (0.65 to 3 g/cm 3 ), temperature (-56°C to 105°C) as per the user's manual data. In this case, forusing an oil sample it merely needs a very compact measuring cell with 2.5 ml of oil. The same oil sample can be used for measurements at 40°C and at 100°C.This will be required to calculate the viscosity index of the deteriorated engine oil to check the level of deterioration detected for important engine oil deterioration parameters. The experimental equipment is washed and dried and then the measured sample in the syringe is attached to it. The measuring cell is lled with the sample from the syringe. The stabilization of the temperature is done automatically and the values of the kinematic and dynamic viscosities along with the density of the sample are recorded rst for 40°C and then 100°C.Once the measurements are completed, the equipment is washed and dried again using its air pump.
A total of180 deteriorated engine oils samples were collected and tested at the engine oil testing facility at Valvoline Cummins Pvt. Ltd., Ambernath, Thane, by using the above discussed laboratory equipment. After the testing was completed, 8 samples were discarded from experimentation on the integrated sensors setup as the deterioration in these samples was much above the permissible limits of engine oil use. The remaining oil samples are analysed and the experimentation of these samples is reported in this research work.
As reported in the earlier published literature(Shinde and Bewoor, 2020b) engine oil samples are collected for different groups such as rst servicing samples, second servicing samples, third servicing along with higher serving oil samples.
As per the servicing schedule for light duty 4-wheeler cars the criteria followed was that the extent of the distance travelled was 10,000kms or a period of 12 months whichever came rst. Out of the total samples collected, 46.1%samples are from the rst servicing period of the vehicles, 37.2% samples are from the second servicing of the vehicles and 16.7% samples are from the third or later servicing periods. A comprehensive database of used engine oils is established. The next part of the discussion is regarding the proposed integrated sensors setup to measure these parameters by the low-cost handy system.

Integrated Sensors Setup Details
The proposed integrated sensor setup to quantify engine oil deterioration has multiple sensors as shown in the schematic representation in Fig. 1 and the photograph of the actual setup is shown in Fig. 2. An integrated setup block diagram shows a high-level view of the encapsulated functional units that make up the system. A block diagram shows the details of the different sensors that have been integrated in the setup. This setup consists of a Fluid Property Sensor FPS2000 sensor which is available for measuring various parameters such as viscosity, density, DC and T f . The next part of this setup consists of two IR sensor transmitter and receiver pairs(IR sensors setup 1 ).A TCS3200 colour sensor is used to measure any change in red colour. Also, another IR sensor transmitter and receiver (IR sensor setup 2 ) for measurement of transmittance is included. ARobo LM35 temperature sensor is tted inside the casing to monitor environmental temperature during the experimentation. This sensor is connected to a CentIoT-MCP2515 and a CAN Bus Module TJA1050 Receiver SPI Module for Arduino. As this sensor is provided with a microcontroller and it operates on the CAN bus protocol, a CAN Bus module is required to read the data from the sensor.
All these sensors are connected to an Arduino Mega 2560 board through an Analog to Digital Connector, where data is collected and analysed for further conversion from hex format to digital format. This data is transferred to Raspberry Pi 4 next where data processing is done and with the GUI programme data is displayed on an LCD. Python programming Thonny Python IDE can be used to code the GUI for displaying the results from the experimentation. Because of the port arrangement of Raspberry pi 4 boards a keyboard and mouse can be connected to the setup so code modi cation can be done easily. Data stored in the csv le format can be transferred to any portable media device. Further by using the latest board, if further collection of testing results of each testing setup is required to be sent to central cloud storage, then it is also possible. Internet of Things (IoT) which will give the user any additional reminders after a speci c time about engine oil change is also possible. The following discussion provides detailed information about each sensor and its use.
The rst sensor is the uid property sensor (FPS) of model: FPS2000 and make: Parker Hanni n Manufacturing (UK) Ltd. The construction, operations and working of the sensor is discussed in an earlier published paper (Shinde and Bewoor, 2020a). This sensor provides important engine oil deterioration parameters such as KV at testing temperature of oil, dielectric constant, density and dynamic viscosity of the engine oil under testing. Dielectric constant is an additional parameter which provides additional information about engine oil deterioration (Turner and Austin, 2003).Previous studies have emphasized that there is an increase in the dielectric constant with a longer distance travelled by the vehicle (Lee andKim, 2002). We need to dip the sensing tip portion of this sensor in the deteriorated oil sample. For experimentation a 10ml oil sample was kept in a glass beaker and it was ensured that the sensing tip was completely immersed in oil.
The second sensor set as shown in Fig. 3is an IR sensor transmitter and receiver pair(IR sensors setup 1 ) xed near both ends of a glass tube with Te on supports(Shinde and Bewoor, 2017). The IR sensor pair is placed exactly at a cross position to the glass tube such that the sensors can sense fresh engine oil which is lighter in colour and also, they can easily detect dark engine oils which are beyond the deterioration range or just near to that range. In the nal setup 1 te on supports are painted with black colour so the effect of lights in an electronic circuit will not affect the response of the IR sensor. Large chamfers at the sensing area around tube are provided to improve detection of fresh engine oil. Also, tuning of the distance between the IR transmitter and receiver is important. For the exact detection of fresh oil samples, we have to check if any bubbles are present in the glass pipe while pouring the oil through the ask and hence a funnel with a larger diameter and a silicon tube for connection to the glass tube are selected. So as soon as the oil passes from rst pair of IR sensors the time count starts and when the oil reaches the other end the second pair of IR sensors stops the time count.
Hence by using these sensors we can calculate the time required for the ow of the oil at room temperature by using formulae to calculate the KV. For validation of the sensor set operation, readings are taken at a constant temperature i.e., at 28°C and at variable room temperature. Details about this aspect are discussed in the result and discussion part of the paper. Time in milliseconds is the output and it is measured by the IR pair which is used to calculate the KV mathematically. If time is the parameter deciding the output, then in this method sensitivity analysis for this sensor type will not be necessary.
The third sensor set IR transmitter and IR receiver pair (IR sensor setup 2 ) is tted on the top and bottom surfaces of the right side of a black colour plastic enclosure as is displayed in Fig. 4.The effect of the ambient light can be avoided by providing a separate enclosure for optical measurement that is the change in transmittance. The working principle with a schematic representation is discussed for the rst prototype in a research paper (Shinde and Bewoor, 2020b). Light from the IR transmitter is transmitted through the deteriorated engine oil sample towards the IR receiver. Some portion of the light is absorbed or has resistance to pass through the deteriorated engine oil because of the change in the physical and chemical properties. Hence, the intensity of light is different at the IR receiver is converted in corresponding resistance in terms of mv. The IR sensor setup 2 showsa sensitivity of 0.0365 for measurement of transmittance (mv).
The fourth proposed sensor is the RGB colour sensor TCS3200 with programmable colour light-to-frequency converters that combine con gurable silicon photodiodes and a current-to-frequency converter on a single monolithic CMOS integrated circuit. To the best of the authors' knowledge the RGB sensor has been used for the rst time for measuring oxidation. The output is a square wave (50% duty cycle) with a frequency that is directly proportional to the light intensity (irradiance). The full-scale output frequency can be scaled by one of three present values via two control input pins. Because of the digital output and digital inputs, direct interaction with microcontroller or other logic electronics is possible. An 8 x 8 array of photodiodes are used in the TCS3200. Each 16 photodiodes have red lters, blue lters, green lters, and no lters respectively. As per the datasheet it has a higher relative responsivity for red colour between 600 to 800nm wavelength. This has a black ring around the sensing area of the sensor. This colour sensor is tted on the left side of the black colour enclosures as shown in Fig. 5. For experimentation we need a 1 mm thick oil lm in a white colour plastic container. The oil sample is positioned exactly below the colour sensor every time for consistency in reading. The colour sensor shows a sensitivity of 0.051 for a range from 570 mv to 400 mv i.e., till 50% deterioration level in terms of oxidation.; but if it shows a sensitivity value of negative 0.165 that means the obtained results show that the oil sample is almost at the cease of its usable life and is almost constant in terms of oxidation value. Figure 6 shows a simulation model of the engine oil degradation of various parameters.
Based on discussions of the methods and materials used, mathematical models that represent lubrication oil degradation due to oxidation, nitration and KV 0 that was induced in a laboratory in terms of KV are shown. Given that the experimental method has some inherent disadvantages such as a limited scope of degradation coverage, unavoidable test errors and longer periods of pre-installation training time, it is possible to use mathematical models to simulate the actual health status of the oil samples by making use of a sensor output that re ects the inputs of all sensors.Multiple devices were utilized to observe engine oil degradation in terms of oxidation, nitration, and alteration in the transmittance measurement.The next section contains the discussion of the results.

Results And Discussions
The data for permissible limits for both, oxidation (abs/cm) and nitration (abs/cm)are 25 (abs/cm)and have been provided by Valvoline Cummins Private Ltd., the manufacturers of engine oils. For any value above that, the engine oil (5W30) has to be changed. According to published literature (Gołębiowski et al., 2018), the oxidation[abs/(0.1 mm)] has to be less than 0.4 i.e. 40 (abs/cm). The allowable limit for engine oil use based on KV is ± 15% compared to fresh engine oil. Depending on this information the following Table I display the deterioration level scale to measure the degradation level of engine oil for parameter KV 0 . Similar to that Table II shows the deterioration level scale for nitration and oxidation. This scale will give a clear idea of whether the engine oil under testing can be used for any further RUL.
Referring to this scale % deterioration levels as compared to unused (fresh) oil can be speci ed. First, the experimental observations on multiple regression analysis for KV 0 measured at 40°C by a Viscometer are compared with KV 1 at T f and are presented in Table III. This multiple regression analysis proves that the P-value of the experimental data is under the acceptable limit. R 2 = 0.93, correlation for 95% con dence level shows fairly good correlation between both methods of measurement for KV.
From the experimentation we get multiple regression Eq. 1 between the laboratory accurate method for KV 0 and KV 1 at T f : Where, X 1 is KV 1 measured at T f . Similar to the above method, simple regression analysis between the KV 0 measurement at 40°C is compared with the KV 2 by calculation for the time needed for the oil to ow throughIR sensors setup 1 at 28°C i.e., at constant temperature in the laboratory. It is presented in Table IV.  Where, X 3 is KV 2 at T f in °C.
Sensor measurement validation for the analytically calculated value of the kinematic viscosity measured by IR sensor for for 28°C or kinematic viscosity measured by IR sensor for uid temperature and kinematic viscosity at uid temperature is shown in Fig. 7. These analytically calculated values are to calculate KV at 40°C is plotted verses KV 0 measured at 40°C.Also, results obtained by both sensors i.e., KV 2 at T f and KV 1 at T f verses KV at 40°C by viscometer are presented by graph in Fig. 8.
Results obtained analytically using equations 1,2 and 3 are demonstrated graphically in Fig. 7 which shows that results obtained by both sensors are comparable whereas results obtained by the IR sensor pair setup 1 show the highest correlation of R 2 = 0.96. Using these two methods for the integrated sensor setup, we can have two versions. Version 1 will have only the low-cost IR sensor pair setup 1 for calculating the KV in the eld trial. In version 2 we can have both sensors installed as discussed in this research work. By using version 1 the cost will be reduced but, there are some limitations of version 1 such as the DC value for that sample will not be available. Using version 2 the deteriorated engine oil sample, which has a higher level of soot or due to other deterioration parameters, can be identi ed with better accuracy. KV 1 will not be accurate at the higher deterioration level because it works on the turning for k sensing method, where, very same displacement amplitudes at the resonator surface with comparatively high frequency are observed.
This shows an altered (e.g., non-Newtonian) measured viscosity behavior when analyzed to a current rotating viscometer evaluation. As a result, the sensor output has no correlation with a classical viscosity test in engine oil and contains high molecular weight viscosity modi er ingredients. This occurs as sensing probes an oil surface and will not nd any effects induced by structural or complex interactions with related typical lengths equal to or higher than the acoustic wave's depth of penetration in the oil (Jakoby, 2005).
Used engine oil samples that were gathered from the rst servicing and tested by the viscometer showed that 61 samples had deteriorated i.e.,74.4% samples had deteriorated out of 82 samples. 46 samples from the second servicing had deteriorated out of 66 samples i.e., 69.7% samples had deteriorated. From the third and later servicing schedule 21 samples were found to have deteriorated for KV out of 28 samples i.e., 75%. This shows that considering all engine oil samples 72.7% samples had deteriorated and had to be replaced. However, the focus of this experiment is on engine oils which have not deteriorated and would still be replaced following standard procedure.
The measurement information of the FPS sensor is not adequate to cover the samples at the far end of the range making it necessary to use the IR sensors setup 1 .A combination of measurements from the FPS sensor and theIR sensors setup 1 leads to good results, even if the improvement is negligible.
The second experimental ndings were for the measurement of oxidation (abs/cm) with respect to the red colour frequency output measured by the colour sensor (C R ). During experimentation, engine oils which had deteriorated equal to or above the oxidation value 35(abs/cm) were removed from the analysis because these were deteriorated oil samples which could have affected our conclusion. We have considered a range of 40% above the deterioration level of 25(abs/cm). Figure 9 shows a plot for experimentation results displaying the change in oxidation versus variation in C R .
Simple regression analysis between oxidation (abs/cm) measured in the laboratory versus alteration in C R for degraded oil samples is carried out and presented in Table VI. Referring to the experimental investigation plot shown in Fig. 9 the linear correlation coe cient shows R 2 = 0.86. Taking that into consideration and also the P-value and other statistical results of the regression analysis as shown in Where, X 4 is the C R at room temperature. The value of X 4 can be used to calculate the oxidation value by an analytical method.
Used engine oil samples collected from rst servicing tested by FT-IR spectroscopy showed that 2 samples had deteriorated i.e., 2.4% samples had deteriorated out of 82 samples. 4 samples had deteriorated out of 66 samples i.e., 6% samples had deteriorated from the second servicing schedule. From the third and later servicing schedule 1 sample had deteriorated for oxidation out of 28 samples i.e., 3.57%. This shows that considering all engine oil samples for KV and oxidation 72.7% samples had deteriorated and had to be replaced. However, we need to focus on engine oils which had not deteriorated but still had to be replaced following standard procedure.
The third experimental ndings are for measurement of nitration (abs/cm) with respect to transmittance (mv) value measured as output of the IR sensor setup 2 . During experimentation engine oils which had deteriorated to equal or above the nitration value of 45(abs/cm) were removed from the analysis because these had deteriorated oil samples which could have affected our conclusion. We have considered a range of 50% above the deterioration level25(abs/cm). Figure 10 shows the results plot of the experimentation undertaken for the change in nitration to variation in transmittance (mc) output by the IR sensor setup 2 .
Simple regression analysis between nitration (abs/cm) measured in the laboratory versus T IR2 for degraded samples of oil is carried out and presented in table VII. Referring to experimental investigation plots and regression analysis between nitration and T IR2 and the linear correlation between data a good correlation coe cient of R 2 = 0.93 is observed, where the P-value of the analysis is below the recommended value of 0.01. Hence, with more than 95% con dence level we can have a linear correlation trade line to derive a mathematical model between the two parameters presented in the above table VII and Fig. 9, which is shown in Eq. 5.
Where, X 5 is the T IR2 (mv) value at room temperature. The value of X 5 is used to calculate the nitration value by an analytical method.
The following discussion for the nitration parameter related to the said engine oil samples collected from the rst servicing tested by FT-IR spectroscopy showed that 25  To the best of the authors' knowledge, it for the rst time that such a large number of oil samples have been used in the experimentation. Also, during eld trials usually information about oil kilometer at that servicing schedule can be easily available as compared to the number of servicing done before the current servicing schedule.When comparing our results to those of older studies, it must be pointed out that taking in to account the effect of random eld collected samples for experimentation this proposed integrated sensor setup provides detailed information of KV, oxidation and nitration. Using multiple regression analyses of data collected from all the sensors and input from users as to the oil kilometers to quantify the engine oil deterioration in terms of KV is reported in the next part of the discussion. The multiple regression equation is shown by Eq. 6 and analysis details are provided in table VIII. Where, O = O km , T = T f ,X 1 = KV 1 , X 3 = KV 2 , X 4 = C R , X 5 = T IR2 and D = DC.
The Eq. 6 and the statistical analysis together, con rm that by using Eq. 6 we can calculate the engine oil KV 0 at 40°C similar to a viscometer, a precision and accurate instrument used in laboratory, to quantify engine oil deterioration by using a mathematical model technique. This delivers signi cantly better results due to the integrated sensor setup approach for experimentation. A large number of existing studies in broader literature has examined and reported that KV is an important engine oil parameter because if there is deterioration beyond the speci ed limit as stated by the standards the friction between engine components will de nitely increase which will in turn affect its performance. Now using the Eq. 6 to quantify engine oil deterioration all the samples which are found to be deteriorated by laboratory methods are exactly all the samples that are shown to be deteriorated by analytical calculations. Along with that, all the samples which showed a 99% deterioration level in laboratory experimentation are almost found to have deteriorated to the same level by the integrated sensor setup. Therefore, the output for the integrated sensors setup using Eq. 6 needs to be veri ed on a new scale which is provided below: The measurement of the engine oil deterioration using the integrated sensory setup can provide procedures for handling data along with suggestions of logic provided by the information displayed in rows 2 and 3of Table IX. Having determined how much the engine oil has deteriorated, further it will be useful to gure out the remaining useful life.

Conclusions
The research reported in this paper full led the identi ed research gap. Experiemental investigation has been carried out with the randomly collected eld samples of engineoil (5W30). Quanti cation of oil degradation in terms of changes in oxidation and nitration values are obtained. Change in oxidation is showing good correlation (R 2 =0.92) w.r.tooutput measured by colour sensor.The coe cient of determination (R 2 =0.93) con rmed the good strength of the correlation between Change in nitration and transmittance measured by IR sensor setup 2 . It is evident from the experimental investigation that, an integrated low cost sensory system could capture required information by IR sensor setup 2 and colour sensorwith acceptable sensitivity (0.0365 and 0.051 respectively).
This result help to conclude that:  Integrated setup prototype electronic circuit photo Color measurement sensor detail view (TCS3200) Figure 6 Engine oil degradation simulation model for viscosity, oxidation, nitration and indirect methods of measurement by sensors.  Oxidation (abs/cm) versus alteration in C R for degraded oil samples.

Figure 10
Nitration (abs/cm) versus variation in T IR2 (mv) for degraded samples of oil.