Modal Emissions Modeling: A Physical Approach

Abstract

Mobile source emission models currently used by state and federal agencies (e.g., Environmental Protection Agency's MOBILE and California Air Resources Board's EMFAC) are often inadequate for analyzing the emissions impact of various transportation control measures, intelligent transportation systems, alternative fuel vehicles, and more sophisticated inspection/maintenance programs contained in most state air quality management plans. These emission models are based on the assumption that vehicle running exhaust emissions can be represented as integrated values for a specific driving cycle, and then later adjusted by speed correction factors. What is needed in addition to these "regional-type" mobile source models is an emissions model that considers at a more fundamental level the modal operation of a vehicle (i.e., emissions that directly relate to vehicle operating modes such as idle, steady-state cruise, various levels of acceleration/deceleration, and so forth). A new modal-emissions modeling approach that is deterministic and based on analytical functions that describe the physical phenomena associated with vehicle operation and emissions productions is presented. This model relies on highly time-resolved emissions and vehicle operation data that must be collected from a wide range of vehicles of varying emission control technologies. Current emission modeling techniques are discussed and the modeling approach and implementation plan for a new, three-year NCHRP Project entitled "Development of a Modal Emissions Model" are described.Significant improvements are needed in the ability to characterize emissions from vehicles operating in real world conditions and in the models used to generate mobile source emission inventories. Numerous studies have shown that under most on-road operating conditions actual vehicle emissions can differ dramatically from what is predicted by current mobile source emission models (1-5). Understanding of the reasons leading to this discrepancy has improved considerably in recent years, and a more systematic approach to determining mobile source emission inventories is needed. This is particularly true given the conformity requirements of the Clean Air Act Amendments of 1990 and the aggressive implementation of transportation control measures, intelligent transportation systems, alternative fuel vehicles, and more sophisticated inspection maintenance programs contained in most state air quality management plans. Using current methods, the uncertainty of mobile source emission inventories is several factors greater than the impact of most mobile source control strategies.Numerous reasons exist for the present discrepancy between calculated and actual emission inventories: poor mathematical representation of emission control system performance as a continuous function of accumulated mileage or speed; inadequate representation of the active fleet; dated representations of driving patterns and vehicle activities; inadequate treatment of modern closed-loop emission control technology; ...

Heavy-Duty Diesel Vehicle Fuel Consumption Modeling Based on Road Load and Power Train Parameters

“…vehicle road load parameters. All of these components, but the vehicle transmission parameters, can be derived from a relationship for fuel consumption, FR, [7][8][9][10][11][12][13][14][15] where N is engine speed in revolutions per second, V d is the engine displacement in liters, LHV is the fuel lower heating value in kJ/kg, η i in the indicated engine efficiency, k is engine friction in kPa, bmep is the brake mean effective pressure in kPa, fmep is the friction mean effective pressure in kPa, P is the sum of the vehicle tractive power and accessory power both in kW.…”

“…Heavy-duty diesel engine friction and efficiency parameters are determined using a Willans curve methodology (e.g., Heywood 25 ) based on the fuel rate equation and the following definition of fuel mean effective pressure, fuel mep [7][8][9][10][11][12][13][14][15] . The fuel mean effective pressure (total fuel consumed in units of pressure) can be related to the indicated mean effective which is the sum of the bmep and the engine friction [7][8][9][10][11][12][13][14][15] by where is the engine friction.…”

“…However, only until recently with the availability of time-resolved speed, emissions and fuel consumption measurements has this relationship been employed to develop vehicle emissions models [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15] which more accurately estimate emissions from vehicles on any driving cycle. There are two approaches being used.…”

“…There are two approaches being used. One [1][2][3][4][5][6] uses the correlation between vehicle tractive power or vehicle specific power (VSP) with emissions and the second [7][8][9][10][11][12][13][14][15] more complete approach considers all of the major power consumption components, i.e., vehicle tractive power, engine friction and efficiency and transmission efficiency and shift schedule.…”

Optimised speed profile design of a vehicle platoon considering road inclinations

“…traffic information systems, intelligent real-time vehicle control systems, and energy consumption/emissions estimation. [2] proposes a modal-emissions modeling approach based on physical phenomena associated with vehicle operation and emissions. An eco-cruise control system, in which the road topographical data is involved to optimize fuel consumption, is presented in [22].…”