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A DIGITALIZED VALIDATION APPROACH FOR REAL TIME AND REMOTE MONITORING OF AN OFF HIGHWAY VEHICLE PERFORMANCE
ISSN: 0148-7191, e-ISSN: 2688-3627
To be published on November 21, 2019 by SAE International in United States
Event: NuGen Summit
A DIGITALIZED VALIDATION APPROACH FOR REAL TIME AND REMOTE MONITORING OF AN OFF-HIGHWAY VEHICLE PERFORMANCE V.Jagannathan 1.a* , B.Jaiganesh 2.b & S.Sudarsanam 3.c Mahindra & Mahindra Limited, Mahindra Research Valley, Mahindra World City, Anjur PO, TN, India Corresponding author Email- V.JAGANNATHAN@mahindra.com Validation of agricultural tractors is necessary to ensure that these machines perform to their expected potential and are aptly matched with implements. Testing these machineries in real-time while performing activities in the field allows a bigger picture to be seen; the performance data incorporates the effects of many external factors (Soil, Climate etc.). Tractor Performance data apprehending is the vital part of validation. Data acquisition of key performance parameters during field validation in different application/different countries is of utmost importance. Most prevailing methodology in Tractor validation is by capturing the performance parameters such as Fuel consumption, Area coverage, Wheel slip, Engine rpm drop, implement depth of cut, Tractor speed etc. in manual and physical way. These methodologies of capturing performance parameters are tedious, time consuming, involves manpower, not so secured or safe. The readings recorded are subjected to ambiguities, error prone with less accuracy leading to repeated trials. Hence the need arises for developing a data acquisition system to measure, monitor real-time & remote tractor performance at varying machine states during field operations. A DAQ (Data Acquisition System) was developed based on the guidelines and requirements. Sensors were evaluated, selected, tested and validated to read each of key performance parameters. All these selected sensors are connected to DAQ with IOT (Internet of Things). This combination allows us to monitor and transmit data for analysis and action (if required) in a timely manner. DAQ were programmed to automatically collect and store data at preprogrammed time intervals. Real time measurements were evaluated by using software programs which provide logical visualizations of sensor data, web access and the ability to trigger alarms if thresholds or rates of change are exceeded. The benefits of automating all data handling, from sensors to visualizations, alarms, reports and access over the internet are obvious; data are available almost immediately, less time is spent collecting and handling the data (thereby reducing overhead costs) and more time becomes available for evaluating the data. With flexibility of DAQ expansion with more modules more than 50 tractor performance parameters including engine ECU parameters were digitalized. Performance parameter real time monitoring and capturing using data loggers builds more confident as of high accuracy. At present, more than three measurement trial iteration conducted to check constituency and to achieve accuracy of ± 5%, which is brought to ±1% by proposed approach with continuous data logging of minimum of two iteration and thereby 75% time reduced. Contrary to any on road vehicles (Cars and buses), off road vehicles (Tractors) are operated in very remote locations. Network connectivity and loss of data is major concern as all field sites for tractor validation across India & other parts of world. This were few limitations which are overcome with inbuilt storage to store data and with a trigger to upload the data to the server whenever GPRS catches the signal. The uniqueness of this total solution is that during remote monitoring of tractor performance, technical experts from head office guides/instructs the test engineers in field to change the driving pattern for tractor performance parameter optimization. Live video streaming of running tractor in field viewed anywhere in world is further advances with this solution proposed for off-highway vehicle. Through this proposed system, Integration of multiple platform (sensors) to single platform (Hub/Data logger) and to server was established, which is big challenge as all sensors used were of different purpose with different configuration so output from sensors are of different format and this was achieved suitably converting with scripting/algorithm/code for post processing the data in software. Integration of big data analytics with remote data monitoring provided real time analysis upon big data analytics, which simplify strategy for decision making. The objective of the system was to provide meaningful and accurate data from tractors performing tasks in-field. After calibrating and testing the separate components of the data acquisition system, as well as testing the system together, the tractor performance parameter results are satisfactory. Future is to establish the tractor management platform with advanced data analytics of predictive and prescriptive on the data acquired. Key Words: Real time, Remote monitoring, Off-Highway vehicle, Data acquisition system (DAQ), Internet of things (IOT), Engine control unit (ECU)