EcoDrive: A Mobile Sensing and Control System for Fuel Efficient Driving R 張祐瑞 R 傅學俊 R 林聖晏

Outline  Introduction  Related work  Modeling  Algorithm  Experiment setup  Evaluation  Conclusion

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.

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.

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.

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.

Introduction – EcoDrive Components  OBD sensing component  A vehicle dynamics modeling component  An acceleration controlling component

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

Introduction – Two main challenges  Model Vehicle Dynamics based on OBD Parameters  Control Air/Fuel Rate and Vehicular Speed to Improve Fuel Efficiency

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.

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

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

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

Related work  Power transition  OBD parameters  Collected data

Related work Power transition

Continuously Variable Transmission 無段自動變速器

Related work Power transition Step Automatic Transmission

Related work OBD Parameters

油量

Related work OBD Parameters Be used to measure the air intake rate of the engine, and therefore an effective indicator of instant fuel consumption

Related work OBD Parameters Indicate current engine mode Open loop mode during short warm up time Closed loop mode at most of the time

Related work OBD Parameters Be used to adjust the air/fuel rate injected into engine

Related work OBD Parameters 車速

Related work OBD Parameters 引擎轉速

Related work OBD Parameters 油門角度

Related work Collected data Urban: milesHighway: miles

Related work Collected data

Modeling Vehicle Forces

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

Engine Propulsion Modeling (F p )

For SAT(Step Automatic Transmission), R G can be represented as For CVT(Continuously Variable Transmission)

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

Drivetrain Loss Modeling (F l ) The drivetrain loss drops to minimum when the car is driving in moderate speed

Wind Resistance Modeling (F w )

Grade Resistance Modeling (F g ) the grade resistance can be modeled as a combination of forces caused by grade and rolling resistance

Modeling Results +

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 …

Controlling Fuel Injection Rate

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

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

In-Vehicle Setup

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.

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.

Fuel Efficiency Test Results in Urban EcoDrive shows 23% and 19% fuel efficiency improvements than driver 1 and 2, respectively.

10%-40% fuel efficiency improvement But average of 20% more travel time.

Fuel Efficiency Test Results in Highway 1. Compare to Cruise Control. 2. Compare to Human drive.

Compare to Cruise Control

Compare to Human Drive EcoDrive shows more than 10% fuel efficiency than cruise control more than 30% fuel efficiency than human drivers on average.

Travel Time and Fuel Efficiency

Modeling Accuracy

Driving Data Statistic

Urban Road Segment Length

Acceleration Pattern

Trace-driven simulation

Discussion 1.Hybrid Vehicle and Electric Vehicle 2.Instant Fuel Economy Display Is Misleading 3.Impact of Traffic 4.User Experience 5.Limitation

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.