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EcoDrive: A Mobile Sensing and Control System for Fuel Efficient Driving R04922112 張祐瑞 R04944025 傅學俊 R04922116 林聖晏
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Outline Introduction Related work Modeling Algorithm Experiment setup Evaluation Conclusion
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Introduction - Why? Morgan Stanley reported that there could be $158 billion in annual savings in the US, if all cars adopted a smoother driving style.
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Introduction - Contribution The focus of this work has been in the design of a system to improve the fuel efficiency of a vehicle’s drive by sensing, computing, and actuating the acceleration behavior of the vehicle in an autonomous manner, by modeling properties of the vehicle, road conditions, and driving actions.
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Introduction – System and Assumption Eco-Drive A fuel consumption sensing and control system that improves fuel efficiency and reduces carbon emissions Estimates instant fuel consumptions of different driving behaviors based on sensed vehicle parameters from the On-board diagnostics (OBD) port Controls the vehicle’s acceleration and speed to provide a fuel efficient drive on its path.
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Introduction – System and Assumption Assuming there is no other factors that would contribute to a choice of acceleration and speed, e.g., other vehicles, pedestrians, etc. or other obstacles in vicinity Provide the driver a switch which can be pressed to instantly disable EcoDrive.
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Introduction – EcoDrive Components OBD sensing component A vehicle dynamics modeling component An acceleration controlling component
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Introduction – EcoDrive Components A vehicle dynamics modeling component Models various vehicle forces as functions of instant fuel consumption and produces a fuel consumption profile, called Air/Fuel Rate (AFR) profile An acceleration controlling component Utilizes the AFR profile to calculate fuel efficient driving strategies according to speed limit and road conditions Emulates the gas pedal by sending voltage values to the vehicular Electronic Control Unit (ECU) The vehicular Electronic Control Unit (ECU) controls air/fuel injection rate according to the voltage inputs
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Introduction – Two main challenges Model Vehicle Dynamics based on OBD Parameters Control Air/Fuel Rate and Vehicular Speed to Improve Fuel Efficiency
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Introduction – Two main challenges Model Vehicle Dynamics based on OBD Parameters EcoDrive uses the OBD parameters to build an AFR profile, which records instant fuel consumptions of various accelerations under different speeds To this end, EcoDrive models various vehicle forces, including propulsion, drivetrain loss, wind resistance and grade resistance, as functions of instant fuel consumption.
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Introduction – Two main challenges Control Air/Fuel Rate and Vehicular Speed to Improve Fuel E ffi ciency The problem is how to adjust vehicular speeds to travel through a certain distance with the lowest fuel consumption Dynamic programming Each state of the dynamic programming model records the minimum air/fuel cost that allows the car to achieve the current speed at the current location
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Introduction – Two main challenges Control Air/Fuel Rate and Vehicular Speed to Improve Fuel E ffi ciency The problem is how to adjust vehicular speeds to travel through a certain distance with the lowest fuel consumption Dynamic programming Each state of the dynamic programming model records the minimum air/fuel cost that allows the car to achieve the current speed at the current location Once the vehicular speed reaches the target speed, EcoDrive enters a cruising state and commands a constant air/fuel injection rate until the car reaches the pre-assigned distance
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Introduction - Prototype More than 100 miles in both urban and highway environment In urban area, EcoDrive achieves 10%-40% higher fuel efficiency than four recruited human drivers On highway, EcoDrive has over 30% improvements compared to different human drivers In comparison with cruise control, EcoDrive achieves an average of 10% higher fuel efficiency
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Related work Power transition OBD parameters Collected data
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Related work Power transition
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Continuously Variable Transmission 無段自動變速器
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Related work Power transition Step Automatic Transmission
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Related work OBD Parameters
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油量
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Related work OBD Parameters Be used to measure the air intake rate of the engine, and therefore an effective indicator of instant fuel consumption
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Related work OBD Parameters Indicate current engine mode Open loop mode during short warm up time Closed loop mode at most of the time
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Related work OBD Parameters Be used to adjust the air/fuel rate injected into engine
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Related work OBD Parameters 車速
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Related work OBD Parameters 引擎轉速
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Related work OBD Parameters 油門角度
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Related work Collected data Urban: 5000+ milesHighway: 5000+ miles
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Related work Collected data
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Modeling Vehicle Forces
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Vehicles Dynamics Modeling Engine Propulsion (F p ) ◦Function of air/fuel rate (AFR) and gear ratio (estimated by vehicular speed and engine RPM) Drivetrain loss (F l ) and wind resistance (F w ) ◦Function of propulsion when driving in constant speed Grade resistance (F g ) ◦Function of altitude changes (extracted from online elevation dataset) The vehicle force can be modeled as follows
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Engine Propulsion Modeling (F p )
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For SAT(Step Automatic Transmission), R G can be represented as For CVT(Continuously Variable Transmission)
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Engine Propulsion Modeling (F p ) Engine torque is produced by the explosion of air and fuel, therefore, we can use AFR to model engine torque. Where f(v) is monotonically increasing with v Put it all together and get
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Drivetrain Loss Modeling (F l ) The drivetrain loss drops to minimum when the car is driving in moderate speed
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Wind Resistance Modeling (F w )
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Grade Resistance Modeling (F g ) the grade resistance can be modeled as a combination of forces caused by grade and rolling resistance
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Modeling Results +
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Build AFR Profile (A Lookup Table) AFR(v, a) : the air/fuel rate when accelerates at a (m/s/s) under speed v(km/h) Air/Fuel Rate0.0 m/s/s0.1 m/s/s0.2 m/s/s… 1 km/h 2 km/hAFR(2, 0.1) 3 km/h 4 km/h 5 km/h …
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Controlling Fuel Injection Rate
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Computer Controlled Gas Pedal Gas Pedal (drive-by-wire) ◦ Human driver press the gas pedal ◦ The position sensor senses gas pedal position ◦ The gas pedal sends the position value to the Electronic Control Unit (ECU) ◦ ECU controls the volumes of air/fuel injected into the engine EcoDrive Controller (Emulate gas pedal) ◦ It calculates the gas pedal position value ◦ It sends the value to the ECU through an Arduino board
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Driving from A to B by Dynamic Programming D: A-B road segment length V: speed limit S(v, d): minimum fuel cost at distance d with speed v Case 1: The car cruises to state (v + 1, d + 1) S(v + 1, d + 1) = S(v + 1, d) + AFR(v + 1, 0) * time Case 2: The car accelerates to state (v + 1, d + 1) at acceleration ax S(v + 1, d + 1) = S(v, d - dx) + AFR(v, ax) * time
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In-Vehicle Setup
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1.Arduino Uno microcontroller : emulate gas pedal. ◦Construct a mapping between sensor analog voltage outputs and pedal positions. 2.6P FEM Connector : delivering signals from Arduino Uno microcontroller to the ECU. 3.6P MALE Connector : delivering signal outputs from the original gas pedal to the ECU. 4.Switch button : Allows the user to switch the signal read by the ECU between the gas pedal and the microcontroller. ◦Human driving mode. ◦EcoDrive mode. 5.APU platform : sends pedal positions to the microcontroller through serial communication and the microcontroller converts the pedal position values into analog voltages outputs in EcoDrive mode.
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Evaluation 1.EcoDrive road testing results in both urban and highway environments. 2.Vehicle dynamics modeling accuracy. 3.Driving data statistics. 4.Trace-driven simulation.
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Fuel Efficiency Test Results in Urban EcoDrive shows 23% and 19% fuel efficiency improvements than driver 1 and 2, respectively.
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10%-40% fuel efficiency improvement But average of 20% more travel time.
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Fuel Efficiency Test Results in Highway 1. Compare to Cruise Control. 2. Compare to Human drive.
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Compare to Cruise Control
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Compare to Human Drive EcoDrive shows more than 10% fuel efficiency than cruise control more than 30% fuel efficiency than human drivers on average.
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Travel Time and Fuel Efficiency
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Modeling Accuracy
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Driving Data Statistic
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Urban Road Segment Length
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Acceleration Pattern
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Trace-driven simulation
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Discussion 1.Hybrid Vehicle and Electric Vehicle 2.Instant Fuel Economy Display Is Misleading 3.Impact of Traffic 4.User Experience 5.Limitation
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Conclusion 1.This paper introduces EcoDrive, a fuel consumption sensing and control system that assists human driver to drive fuel efficiently. 2.In comparison with human drivers, EcoDrive improves fuel efficiency by 10%- 40% in urban environments. It has an average of 10% higher fuel efficiency than vehicle built-in cruise control and more than 30% fuel efficiency than human drivers on highway. 3.Trade-off between traveling time and fuel consumption.
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