CEE6984: Special Topics – Transportation Sustainability Energy and Emission Models

Course Instruction It is a pre-recorded class with narration. Instructors: Dr. Hesham Rakha (hrakha@vt.edu) Dr. Kyoungho Ahn (kahn@vt.edu) Read the slide first and click the speaker icon to listen audio narration Recommended to use earphone or headphone CEE6984: Special Topics – Transportation Sustainability

Transportation Sustainability The lecture series cover a wide range of transportation sustainability topics. “Energy-Efficient Urban Transportation” Vehicle fuel consumption and emission modeling Vehicle engine basics and powertrain modeling Traffic flow theory basics and vehicle car-following models Fuel-efficient Intelligent Transportation Systems (ITS) and Connected Vehicle (CV) applications CEE6984: Special Topics – Transportation Sustainability

Lecture Objectives Understand the basic concept of vehicle energy and emission models US EPA’s MOVES, VT-Micro, VT-CPFM models Learn how to use energy and emission models using a simple case study CEE6984: Special Topics – Transportation Sustainability

Overview: The transportation sector consumes approximately 30% of the total energy. mostly petroleum-based products including gasoline and diesel fuels. In 2013, greenhouse gas emissions from transportation accounted for about 27% of total U.S. greenhouse gas (GHG) emissions the second largest contributor of U.S. GHG emissions after the Electricity sector. Greenhouse gas emissions from transportation have been increased by about 16% since 1990. CEE6984: Special Topics – Transportation Sustainability

Overview: Accurate estimation of fuel consumption and emission is one of most important tasks to improve the vehicle energy efficiency and cleaner environment. A recent study estimated that teaching consumers to eco-drive can improve actual fuel efficiency by an average of 17%. A simple, accurate, and efficient fuel consumption and emission model is one of the key elements of a real-time eco-driving system (e.g. eco-routing system). CEE6984: Special Topics – Transportation Sustainability

Overview: Emission Inventory – a database that lists, by source, the amount of air pollutants discharged into the atmosphere of a community during a given time period (U.S. EPA) Emission inventories are a mandatory component for the development of an effective air quality management process. CEE6984: Special Topics – Transportation Sustainability

Overview: Three levels of modeling Macroscopic Mesoscopic Microscopic MOVES (U.S. EPA), EMFAC (California Air Resources Board) Mesoscopic VT-Meso: Based on average vehicle speed, number of vehicle stops, and stopped delay. Microscopic Statistical models: VT-Micro Physical models: Based on vehicle power usage VT-CPFM, MOVES (project level), and CMEM. CEE6984: Special Topics – Transportation Sustainability

Energy and Emission Models: MOVES VT-Micro model VT-CPFM model CEE6984: Special Topics – Transportation Sustainability

MOVES: Overview The MOtor Vehicle Emission Simulator (MOVES) estimates emissions for mobile sources covering a wide range of pollutants and allows multiple scale analysis. MOVES was approved for New State Implementation Plans(SIPs) Use MOVES2014 now for any new SIPs If significant work on a SIP with MOVES2010 has already been completed, you can continue Transportation conformity analyses, including Regional conformity analysis Project-level conformity analysis (PM and CO Hotspots) CEE6984: Special Topics – Transportation Sustainability CEE5604

MOVES: Emission Process Running Start Extended Idle (trucks “hoteling” under load) Evaporative Refueling Crankcase Tire Wear Brake Wear CEE6984: Special Topics – Transportation Sustainability

MOVES: Pollutants HC (THC, NMHC, NMOG, TOG, VOC) CO NOx NH3 SO2 PM10,2.5 GHG (CO2, CH4, N2O) Toxics Energy (total, petroleum, fossil) CEE6984: Special Topics – Transportation Sustainability

MOVES: Fuel and Vehicle Types Fuel types Compressed Natural Gas, Diesel, Ethanol (E-85), Liquefied Petroleum Gas, and Gasoline. Vehicle types Passenger Car, Passenger Truck, Motorcycle, Light Commercial Truck, Intercity Bus, Transit Bus, School Bus, Refuse Truck, Single Unit Short-haul and Long-haul Trucks, Motor Home, Combination Short-haul and Long-haul Trucks CEE6984: Special Topics – Transportation Sustainability

MOVES: Emission Rates MOVES estimates a different emission rate for each combination of… CEE6984: Special Topics – Transportation Sustainability

MOVES: Graphical User Interface (GUI) CEE6984: Special Topics – Transportation Sustainability

MOVES: Graphical User Interface (GUI) CEE6984: Special Topics – Transportation Sustainability

MOVES: Input and Output To run MOVES, A run specification file Input database MOVES creates a results as an output database MySQL is typically used to view the results ( Database) and manipulate the results; the information can also be exported to another program (e.g., Excel) CEE6984: Special Topics – Transportation Sustainability

MOVES: Three Scales of Analysis National level Entire nation One or more states One or more counties County level One county A multi-county area Project level An individual transportation project (e.g., a highway, intersection, or transit project) CEE6984: Special Topics – Transportation Sustainability

MOVES: Project Level Analysis CEE6984: Special Topics – Transportation Sustainability

MOVES: Pros and Cons Pros Cons Comprehensive energy and emission model all vehicle types and pollutant types Can evaluate various impacts (vehicle age distribution, fuel types, temperature, I/M program, etc.) National and County level estimation Cons Complexity of Input database Computation time Output formats Not suitable for complex transportation projects Can’t be implemented into microscopic traffic simulation models CEE6984: Special Topics – Transportation Sustainability

MOVES: Further Information http://www.epa.gov/otaq/models/moves/ MOVES - Training Sessions Webinars Hands-on Training Course Project level training for PM hotspot analysis http://www.epa.gov/otaq/models/moves/training.htm CEE6984: Special Topics – Transportation Sustainability

VT-Micro: Overview VT-Micro uses speed and acceleration values as input variables and includes 32 parameters that are calibrated for different vehicles [Ahn et al. (2002) and Rakha et al. (2004)] Exponential transformation ensures positive MOE estimates The model estimates second-by-second fuel, HC, CO, NOx, and CO2 Where: L = Regression constant (a0) M = Regression constant (a<0) u = Instantaneous speed a = Instantaneous acceleration CEE6984: Special Topics – Transportation Sustainability

VT-Micro: Data and Vehicle Types Chassis dynamometer data (ORNL and EPA 97 vehicles) Vehicle types ORNL vehicles EPA Light duty vehicle (LDV): LDVs 1 to 5 EPA Light duty truck (LDT): LDTs 1 to 2 EPA High emitters (HE): HEs 1 to 4 Heavy Duty Truck All data were collected at FTP conditions using the standard vehicle certification fuel. CEE6984: Special Topics – Transportation Sustainability

VT-Micro: Model Validation CEE6984: Special Topics – Transportation Sustainability

VT-Micro: Boundary condition Vehicles have their maximum operating boundary. Vehicle fuel consumption and emission data were measured in a laboratory within the vehicle’s feasible vehicle speed and acceleration envelope. The VT-Micro model should be used within the boundaries used in the model calibration procedure. This performance boundary is extremely important when the energy and emission models are used with microscopic traffic flow models. CEE6984: Special Topics – Transportation Sustainability

VT-Micro: Boundary condition A typical speed and acceleration performance boundary CEE6984: Special Topics – Transportation Sustainability

VT-Micro: Conclusion Current state-of-the-art models estimate vehicle fuel consumption and emissions based on aggregated variables (average speed and distance). Can’t capture transient changes in a vehicle’s speed and acceleration Stop and go driving with average speed of 50 mph and constant speed driving with average speed of 50 mph can generate significantly different fuel consumption and emission rates: Average speed model will generate the same results VT-Micro model Can capture transient changes in a vehicle’s speed and acceleration Can evaluate the energy and environmental impact on various transportation projects and can be easy implemented into eco-driving applications and traffic simulation models. CEE6984: Special Topics – Transportation Sustainability

VT-CPFM: Overview Virginia Tech Comprehensive Power-based Fuel Consumption Model (VT-CPFM) was developed to be implemented into vehicle eco-driving applications and microscopic traffic simulation models. The model is calibrated using: the EPA fuel economy data (city and highway mpg) publically available vehicle specific data without using field collected data. CEE6984: Special Topics – Transportation Sustainability

VT-CPFM: Overview On-board Diagnostic (OBD) data demonstrate: For positive power conditions the fuel consumption function is convex Fuel consumption could be modeled using a second-order polynomial model CEE6984: Special Topics – Transportation Sustainability

VT-CPFM: Overview A second-order model provides a good model accuracy and applicability. VT-CPFM 1 model VT-CPFM 2 model Where α0, α1, α2 and β0, β1, and β2 are vehicle-specific model constants that are calibrated for each vehicle and ωidle is the engine idling speed (rpm). CEE6984: Special Topics – Transportation Sustainability

VT-CPFM: Overview VT-CPFM 1 model utilizes instantaneous vehicle power The power is a function of the vehicle speed and acceleration level and roadway grade Input variables can be measured directly using non-engine instrumentation, e.g. a Global Positioning System (GPS). VT-CPFM 2 model requires engine data in addition to vehicle power Typical fuel consumption models can’t estimate the impacts of gear-shifting. Vehicle’s gear shifting affects the engine speed – results in changes in the fuel consumption rates. This model can be used to estimate the impacts of gear-shifting strategies and can be used with the vehicle powertrain modeling. Both models are ideal for implementation within microscopic traffic simulation software and eco-driving applications. CEE6984: Special Topics – Transportation Sustainability

VT-CPFM: LA92 Driving Cycle CEE6984: Special Topics – Transportation Sustainability

Case Study: VT-Micro model Estimate fuel consumption and emissions for the city test (LA04) cycle with VT-Micro model (LDV3) Use VT-Micro_Model v1.xlsx in the assignment folder CEE6984: Special Topics – Transportation Sustainability

Case Study: VT-Micro model The city test cycle Also referred as the EPA Urban Dynamometer Driving Schedule (UDDS) or LA04 cycle Length: 23 minutes Distance: 11.9 km (or 7.5 mile) Average speed: 31.2 km/h (or 19.5 mph) CEE6984: Special Topics – Transportation Sustainability

Case Study: VT-Micro model CEE6984: Special Topics – Transportation Sustainability

Case Study: VT-Micro model (VT-Micro_Model V1.xlsx) CEE6984: Special Topics – Transportation Sustainability

Case Study: VT-Micro model (VT-Micro_Model V1.xlsx) CEE6984: Special Topics – Transportation Sustainability

Case Study: VT-Micro model CEE6984: Special Topics – Transportation Sustainability

Case Study: VT-Micro model CEE6984: Special Topics – Transportation Sustainability

Case Study: VT-Micro model For the city test cycle, The VT-Micro model predicts: 10.72 km/l or 25.22 mpg Fuel HC CO NOx CO2 Total 1.113 L 0.229 g 4.954 g 1.017 g 3.579 kg Rates 0.093 l/km 0.019 g/km 0.415 g/km 0.085 g/km 0.300 kg/km CEE6984: Special Topics – Transportation Sustainability

Summary: Three fuel consumption and emission models Case study using VT-Micro model Question – Please email to Kyoungho Ahn (kahn@vt.edu) CEE6984: Special Topics – Transportation Sustainability