Steps Towards Cleaner Environment - Development of Delhi Driving Cycle (DDC)

1. Steps Towards Cleaner Environment - Development of Delhi Driving Cycle (DDC) PETROTECH - 2010 Indian Oil Corporation Ltd.

2. Fuel quality up-gradation and vehicle emission norms. • Air quality and emission inventory studies • Need for Delhi Driving Cycle (DDC) • Methodology for Data Acquisition Analysis and validation • Further work proposed • Summary Contents

3. Concern for Human Health is the Driving Force for Emission Norms & Fuel Quality Standards Fuel Quality and Vehicle Technology To meet stringent environmental norms Environmental Regulations Based on Air Quality data AQM & Source Apportionment Studies Measure of Quality of Air Human Health Concern for all

4. Testing Times for Delhi

5. Fuel Quality Related Decisions by Courts and Government of India During July, 1998, Hon’ble Supreme Court directed the Govt. of Delhi to: Increase the public fleet from 6000 to 10,000 buses Convert all the existing fleet of buses to run on CNG by April,2001 Stricter limits for sulphur in fuel Petrol driven vehicles to run on unleaded and low benzene petrol EPCA headed by Sh. Bhure Lal submitted report on Clean Fuels to the Hon’ble Supreme Court. LPG allowed by Government as an automotive fuel. MoP&NG introduced 5% ethanol blending in gasoline.

6. During Sept, 2001, Government of India set up an expert committee to recommend an Auto Fuel Policy and to devise a road map for its implementation in the country To recommend suitable auto fuels for the country and their specifications considering their: Availability and logistics Economics & possibilities of multi-fuel use in different categories of vehicles Recommend automobile technology for ensuring minimization of the social cost of meeting the norms. To recommend fiscal measures including; Removing pricing distortions fiscal interventions & Use of market based instruments etc. To recommend institutional mechanisms and enforcement measures. Expert Committee for Auto Fuel Policy (AFP)

7. Observations of Expert Committee • Little work done in the country on Air Pollution Source inventory and Apportionment and therefore Studies should be undertaken on an urgent basis • Data in regard to proportion of vehicular emissions related morbidity & its impact on health are insufficient • Petrol and Diesel are major auto fuels and they should be of the right quality • In-use vehicles are not properly maintained and mechanism to check the working of Emission control devices is weak

8. Recommendations of AFP • Undertake the Air Quality Monitoring and Source Apportionment Studies for the Entire Country • Data base linking air pollution / vehicular emissions related diseases should be created • Automotive fuel economy standards to be declared • Liquid Fuels to continue as main fuels & Alternative Auto Fuels CNG/LPG may be promoted in select polluted cities • Efficient PUC and I&M System for in-use vehicles • Anti Adulteration Measures to be taken by OMCs

9. Roadmap as Per Auto Fuel Policy India to follow the Euro equivalent norms for fuel quality and vehicle emission upto year 2010 ENTIRE COUNTRY BHARAT STAGE-II 1ST APRIL 2005 EURO-III 1ST APRIL 2010 EQUIVALENT METROS & MAJOR CITIES (BANGALORE, HYDERABAD, AHMEDABAD, PUNE, SURAT, KANPUR, AGRA, LUCKNOW AND SHOLAPUR) BHARAT STAGE-II 1st April 2003 EURO-III 1st April 2005 EQUIVALENT EURO-IV 1st April 2010 EQUIVALENT Auto Fuel Policy recommends that beyond 2010, India to have its own fuel quality and vehicular emissions norms based on the Air Quality Monitoring and Source Apportionment Studies

10. Air Quality Studies in Six Cities Oil industry initiated the air quality studies in 6 cities in collaboration with NEERI, ARAI, TERI & IITs and has been completed under the supervision / technical guidance of CPCB with following objectives, Identification of critical pollutants and sources of pollution. Assessment of pollution loads from different sources and contribution of auto exhaust. Vehicle pollution from different categories of vehicles and effect of change in vehicle technology, fuel quality improvements, use of alternative fuels etc. Identification of %age share of each emission source including automobiles in major cities imperative before initiating the capital intensive up-gradation of refineries

11. Automotive Emission Inventory for Source Apportionment Studies The automotive emission inventory for source apportionment studies calculated by testing different vintages of vehicles on Chassis Dynamometer Emission factors for each category of vehicles derived from Mass emission testing Driving conditions simulated using the European Driving cycle for passenger cars However, Indian situation is unlike that of Europe in terms of following; Vehicle density and Driving Pattern Road Infrastructure Inspection & Maintenance Enforcements Vehicle/engine Technology

12. New Delhi Driving Cycle (DDC) Observations of Steering Committee Existing driving cycle adopted from Europe No representation of ground reality Realistic assessment of emission factors for vehicles to be ensured after considering the changing city dynamics (flyovers) and mode of transport (Delhi Metro) IOC R&D volunteered to undertake the development of DDC Steering Committee Meeting for Air Quality Monitoring held during Oct’07 12

13. Driving Cycle • A driving cycle is a speed-time sequence to represent the driving pattern of a category of vehicles plying in the specific city for • measurement of automotive exhaust gas emissions, and • To monitor fuel consumption under simulated conditions In general, it is believed that vehicles while traveling in the city, experience this driving pattern repetitively throughout their journey

14. Types of Driving Cycle Transient Driving Cycle • Based on the actual road data over the whole length of the route • Application of statistical tools for selection and rejection of collected data • No repetitive patterns • US-EPA – FTP 72, FTP 75 are typical examples Synthetic Driving Cycle • Based on distinct segments of modes like cruising, acceleration, deceleration and idling etc. • Repetitive patterns combined to form one cycle • Examples include ECE15, EUDC, MIDC, IDC etc.

15. National / International Driving Cycles US Driving Cycle Continuous Cycle for 1800 sec Presents the actual driving pattern on road European Driving Cycle Synthetic Cycle Repetition of patterns IDC by ARAI – Year 1986 Synthetic Cycle - combination of driving cycles of different cities Bangkok & Tehran Driving Cycle Delhi Bus Driving Cycle Worldwide Harmonised Motorcycle Test Cycle(WMTC) • Driving Cycle influenced by: • Driving behaviour • Vehicle type • Traffic conditions (density and volume) • Driving route • Climatic Conditions • Duration & Frequency of driving Each country has developed its own driving cycle depending on their traffic conditions and road network

16. Driving Cycles in India 2/3-Wheelers Passenger Cars • Adopted from Europe in year 2000 • Doesn’t represent the Indian driving conditions due to vide variations in Traffic density, road conditions, driving habits etc. • Developed by ARAI in 1986 • Too old to represent the actual road conditions

17. Need for Delhi Driving Cycle (DDC) Changing traffic patterns, driving habits, modes of transport, road infrastructure, construction of flyovers and metro rail affect the realistic assessment of Automotive inventory for different cities including Delhi Realistic assessment of vehicular emission load is only possible when the emission testing is undertaken following a representative driving cycle on the chassis dynamometer A step towards development of new Indian driving cycle after developing driving cycles for different cities Guiding tool for deciding Future Fuel Economy Standards and Emission Legislations Assess proportional benefits of fuel quality viz-a-viz engine technology before initiating any technological modifications in the refineries requiring huge capital investments 17

18. Components of Delhi Driving Cycle • Route Selection- identify the representative routes for the city of Delhi • Vehicle Selection – to be inline with market share and size • Equipment Selection – for recording the on-road data • Data Collection and Analysis – field trials on selected routes and during defined time-slots • Validation of Final Driving Cycle on chassis dynamometer • Comparison with Modified Indian Driving Cycle (MIDC)

19. Route selection practices in Vogue

20. Route Selection - IOC’s Approach • Route Selection Criteria primarily based on home to work trips concept considering • Traffic density of individual vehicle category • Land use pattern • Total Traffic volume of Delhi available from SIAM/RTO • Division of Delhi in 3 major zones • Inner Delhi, Middle Delhi and Outer Delhi • Identify different sites across the city based on major zones

21. Division of Delhi in 3 Zones Middle Inner Outer

22. Identification of 51 major traffic sites Source: CDP-Delhi (2007), Transport Demand Forecast Study & development of integrated multi-modal public transport network for NCT of Delhi, Interim Report, July 2007 and Air Quality Monitoring Sites in Delhi

23. Locating Landmarks • Categorizing major landmarks near each site • Based on residential area, commercial area, shopping complexes, Hospitals, Universities, Schools, Colleges, railway stations, bus terminals, airports, religious places, flyovers and major connecting roads • Assigning of weighing factors to traffic flows and different time slots • Peak and off-peak hours • Weekdays and weekends Seven representatives routes formed based on the categorization of major landmarks near the identified 51 sites

24. Weighing Factors for Routes and Time Slots • 3 sites selected on each route for traffic monitoring • On each site, traffic monitoring exercise completed for 3 days • Manual data counting by the professional agency for 16 hours a day • Total traffic flow for each route and each time slot calculated for both the directions • Normalized weighing factors calculated for individual routes and time slots

25. Route Selection - Current Methodology • Focus on the formation of representative driving pattern based on typical daily traffic flow scenario in Delhi • Selected routes are based on the land use pattern and travel demand • Major business routes, arterial, sub-arterial roads, flyovers, under-bridges, drive-way lanes and intersections covered • Metro construction avoided to a larger extent • Traffic influx / efflux from/to other cities of NCR duly considered • Vehicle trials covered the lean, average and peak conditions of road traffic • The week-ends also formed a part of vehicle trial • Weighing factors assigned to each route, each day as well as each time slot during the day

26. Vehicle Selection Criteria Since the driving cycle is influenced by the size of the vehicle, the selection of the vehicle was done based on its class & fuel type • Vehicle Make • Model • Class / Size • Engine Type • Displacement • Power / Torque • Fuel Economy / Mileage • Fuel Type • Gasoline • Diesel • CNG / Dual Fuel** • LPG / Dual Fuel** **Not considered due to non-availability in-line fuel consumption meter for gaseous fuels 4 vehicles (2 gasoline and 2 diesel) selected for the study

27. Data Measurement & Acquisition for DDC GPS Sensor Data Logger Fuel Consumption Meter Wheel RPM Sensor Speed Sensor Engine rpm Sensor

28. Data Acquisition on 7 Routes • 4 No. of vehicles used (2 gasoline and 2 diesel) • Data acquisition continued for 120 days • All the vehicles covered seven routes for six days during four time slots (peak and off-peak hours) • No. of trips = 224 • 4 Weekdays per week • 2 Weekends per week • Timings of field trips • 4 times a day • Peak hours - 8:00 – 10:00 AM, 5:00 – 7:00 PM • Off-peak hours – 12:00 – 2:00 PM & 8:00 – 10:00 PM

29. Data Analysis • All the data acquired during field trials segregated into microtrips • Microtrip is a speed profile of the vehicle between two successive idling periods • Statistical parameters like avg. speed, % idling, % cruising, % acceleration and % deceleration calculated for complete raw data and each microtrip • Microptrips classified into congested, semi-urban, urban and extra-urban traffic flow categories based on statistical parameters • Most representative microtrps selected from each traffic category • Weighing factors applied to these microtrips • Driving cycle constructed after calculating the time of each traffic category in the final driving cycle

30. Delhi Driving Cycle Speed (kph) Time (sec) Total Duration – 1561 sec Max. Speed – 60 kph

31. Comparison of Characteristics of DDC with Raw Data DDC very closely represents the Raw Data acquired during the road trials

32. Comparison of DDC with MIDC

33. Validation of DDC based on Fuel Economy DDC represents the real on-road conditions better than existing driving cycle (MIDC) for passenger cars

34. Key characteristics of DDC • Average speed including idling is 17.9 kph which matches with the on-road data • The acceleration / deceleration / idling and cruising characteristics matches with the on-road data • Fuel Economy of the selected driving cycle matches with the on-road FE of different vehicles • Maximum speed of 60 kph is also representative of the actual driving conditions in Delhi Delhi Driving Cycle is representative of the actual running conditions of the passenger cars in Delhi city

35. Further Work Proposed • Further fuel economy and emission data to be collected through on-line emission measurement in the field and comparison with simulated DDC in the lab on various categories of vehicles. • Studies for actual population of vehicles and average distance travelled in various studies. • Estimation of vehicle pollution load vis-à-vis pollution load from other sources. • Estimate of fuel economy and emission reduction possible through better maintenance practices. • Assessment of the need for stricter fuel quality and emission norms.

36. Summary • Fuel quality and emission norms in India have been traditionally based on European Standards • The actual road driving conditions in Indian cities much different from Europe • Calculating vehicle emission load on the basis of European test cycle does not give realistic picture and hence need for Indian specific data was felt by Expert Committee which recommended earlier Auto Fuel Policy (AFP) • Development of DDC by IOC R&D is an important step which will facilitate accurate assessment of the actual pollution load in Indian cities which can act as a guide for future fuel quality and emission norms in India

37. Thank You malhotrark@iocl.co.in

38. Preliminary Findings of Air Quality Studies in Six Cities Particulate emission (Pm10) is of major concern in the metro cities. The major sources of Pm10 emissions across various cities are road dust, industry, domestic and vehicular emissions. The share of vehicular emissions varies considerably from city to city: 6% in Mumbai, 7% in Delhi, 14% in Chennai, 18% in Pune, 21% in Kanpur and 41% in Bangalore. In the city of Delhi, Pm10 emissions is very high (147.2 TPD) and road dust accounts for 52.50%. The contribution from Transport sector is 6.59% as per the Emission Inventory. More than 50% of Pm2.5 emission is from domestic sector (LPG) with ~ 7.0% contribution from transport sector.

39. National / International Driving Cycles US Driving Cycle Continuous Cycle for 1800 sec Presents the actual driving pattern on road European Driving Cycle Synthetic Cycle Repetition of patterns IDC by ARAI – Year 1986 Synthetic Cycle - combination of driving cycles of different cities Bangkok & Tehran Driving Cycle Delhi Bus Driving Cycle Worldwide Harmonised Motorcycle Test Cycle(WMTC) • Driving Cycle influenced by: • Driving behaviour • Vehicle type • Traffic conditions (density and volume) • Driving route • Climatic Conditions • Duration & Frequency of driving Each country has developed its own driving cycle depending on their traffic conditions and road network

40. Route selection practices in Vogue

41. Route 1A Distance 11 km 41 Shankar Road to Windsor Pl. via Rajinder Nagar, Jhandewala, C.P and Janpath

42. Route 1B Total Distance – 14 km 42 Patparganj to ISBT via Geeta Colony, Inner Ring Road and Dariya Ganj

43. Route 1C Total Distance – 18 km Noida Link Road to N.D Railway Station via Akshardham, Ring Road, Barahkhamba, Outer CP and Minto Road 43

44. Route 1D Total Distance – 19 km 44 Mehrauli Badarpur to Mathura Rd. via Press Enclave Marg, IIT and Moolchand

45. Route 1E Distance 20 km 45 Janakpuri to Airport via Inner Ring Road, Dhaula Kuan, and NH8

46. Route 1F Total Distance – 21 km 46 Mukharjee Nagar to NH1 via Azadpur, Shalimar Bagh, Pitampura and Rohini

47. Route 1G Total Distance – 17 km IIPM to IFFCO chowk via Mahipalpur, Vasant Kunj, JNU, IIT, Saket and Lado Sarai 47

48. Flow-chart for Data Analysis Form the Speed Acceleration Matrix (SAM) for the raw data based on frequency of occurrence of speed and acceleration (Speed interval 5 kph, Accel/Deccel Interval – 1 kph/s) Collect the Raw Data from the trials Differentiate the speed data to get the acceleration in (km/hr)/s Calculate the Target Parameters from the normalized base data Calculate the Target Parameters from the normalized raw data Normalize this raw data based on percentage basis Segregate the data obtained during the trials into microtrips Calculate the average speed of each microtrip Prepare the SAM for each microtrip Based on the average speed and % idling divide these microtrips in to congested, urban, extra urban and highway categories Calculate Vrel = Vmt/Vtotal for each microtrip Normalize the data obtained from each microtrip Select the microtrips having the least sum of Ni's in each category For each microtrip i calculate Ni = |VRELi - 1| + |% IDLE TIMEi - 1| Calculate % idle time rel = % idlemt / % idle total Calculate the average parameters of these selected microtrips of each category by forming the normalized table Identify the microtrip having similar parameters to these average parameters in each category Calculate following parameters - %idling, %de-accel, %accel, % cruising & average speed. Store this data for each selected microtrip Combine these microtrips of each category to form the driving cycle having the parameters equal to the target parameters