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To promote real time monitoring, In use performance ratio monitoring “IUPRm” checks has been enforced in India from Apr’23 as a part of BS6-2 regulation. Since IUPRm is representative of diagnostic frequency in real driving conditions and usage pattern. therefore, a clear understanding of real-world driving is required to define IUPRm targets. This paper shares methodology and Validation steps for defining IUPRm routes for Indian market. Methodology objective is to standardize the market operating conditions over a particular region. Selected Methodology consist of three steps: For defining IUPRm route framework, first step is to have a pre-market survey to know current In use performance ratio “IUPR” status and improvement areas in existing market vehicles. Second step is to define market representative localized on road routes based on the finding of Pre-market survey.

To promote real time monitoring, IUPRm checks has been enforced in India from Apr’23 as a part of BS6-2 regulation. Since IUPRm monitoring is representative of diagnostic frequency in real driving conditions and usage pattern. Therefore, a clear understanding of real-world driving is required to define IUPRm targets. This paper shares methodology and Validation steps for defining IUPR routes for Indian market. Methodology objective is to standardize the market operating conditions over a particular region. Selected Methodology consist of three steps: For defining IUPR route framework, first step is to have a pre-market survey to know current IUPR status and improvement areas in existing market vehicles. Second step is to define market representative localized on road routes based on the finding of Pre-market survey. Third step is to validate defined IUPR routes and correlate the output in reference to coverage of market operating conditions.

Indian automobile industry is set to witness the biggest emission reforms of the last two decades with the implementation of BS6 emission norms from 1st April 2020 and Real Driving Emissions (RDE) from 1st April 2023. However, there are still a lot of unanswered questions regarding the test procedure of RDE for India. For India, adopting European RDE test procedure as it is may be a challenge because of the significant differences between India and Europe in terms of weather, geography, demography, road infrastructure, driving behavior and fuel quality. This paper discusses the detailed experimental results of Real Driving Emission tests analyzing after-treatment system configurations (LNT, sDPF, ufSCR) considering different scenarios such as test routes, test days, driving behavior etc. Variation in trip dynamics (Severity, Softness in driving), trip validity and normality and post-processed results are other key points of interests investigated.

Automotive manufacturers are striving to improve the real-world driving experience for customers. To provide the better overall performance like fuel economy, we must have the real world driving behavior of our customers. The driving behavior of customers may change from city to city or region to region. Thus to make a real representative driving behavior of customer for each different region becomes tedious task. The present paper describes a detailed methodology to make a representative driving pattern quickly based on a Matlab script. The vehicles were driven in major Indian cities (Delhi, Mumbai, Nasik and Pune). The data was recorded with a frequency of 1 Hz. This data is segregated into different short trips. These short trips are grouped together based on maximum vehicle velocity in each short trip & velocity acceleration frequency distribution. Velocity acceleration frequency distribution of individual short trip is compared with each other quantitatively using Matlab script.

In the Indian Context, Fuel Economy of a vehicle is one of key elements while buying a Car. The fuel economy declared by OEMs (Original Equipment Manufacturers) is one of the key indicators while assessing the fuel economy. However it is based on a standard driving cycle and evaluated under standard conditions as mandated by emission legislation. As the driving pattern has a major influence on fuel economy, the objective of this paper is to study real world driving patterns and to define a methodology to simulate a real world driving cycle. A case study was done on Delhi City, by running a fleet of vehicles in different traffic conditions. Thereafter data analysis like acceleration %, specific energy demand per distance, Acceleration vs. Vehicle Speed distribution etc. was done with the help of MATLAB. The final validation of cycle was done by comparing Lab results with on-road Fuel Economy data.