CARMA: Towards Personalized Automotive Tuning

CARMA: Towards Personalized Automotive Tuning Tobias Flach1, Nilesh Mishra1, Luis Pedrosa1, Christopher Riesz2, Ramesh Govindan1 1 University of Sout...
0 downloads 2 Views 5MB Size
CARMA: Towards Personalized Automotive Tuning Tobias Flach1, Nilesh Mishra1, Luis Pedrosa1, Christopher Riesz2, Ramesh Govindan1 1 University

of Southern California 2 Rutgers University, Camden Campus

Sensys 2011

Introduction Networked Sensing  Smart Grid  Smart Building

Smartphones  Context awareness  Participatory sensing

Automobiles  On-board sensing  Personalized tuning Introduction

Motivation

Architecture

Evaluation

Conclusion

2

Sensing and Control in an Automobile

Automobiles are highly customizable but this capability is not exposed to the user http://www.memsindustrygroup.org/files/public/April2010.htm

Introduction

Motivation

Architecture

Evaluation

Conclusion

3

Current Practice: Fixed Control Parameters Driving behavior

Terrain

Factory defaults cannot cover all possible conditions Traffic

Introduction

Weather

Motivation

Architecture

Evaluation

Conclusion

4

Our Goal: Flexible Personalized Tuning

Alice CarMA canBob optimize for individual trips

Introduction

Motivation

Architecture

Evaluation

Conclusion

5

Can Personalized Tuning Be Effective?

Interstate Route

Hill Route

Street route

Impact of route characteristics? Impact of driving behavior? Introduction

Motivation

Architecture

Evaluation

Conclusion

6

Can Personalized Tuning Be Effective?

Intrinsic variability

Extrinsic variability

Fuel economy for two cars on different routes (with different conditions)

Introduction

Motivation

Architecture

Exploitable by personalized tuning

Evaluation

Conclusion

7

Background: Scanning and Tuning

Client device

On-board diagnostics (OBD-II)

Sensor

Table: Desired Idle RPMValue

Coolant absoluteTransmission not Intake manifold pressure engaged RPMTemperature

32.0Transmission kPa engaged 1925 rev/min

-20°C Speed 0°C timing advance1106.05 Ignition

1200km/h 16.0 964.65 3.0 °(relative)

Scanning… Tuning… 1200

20°C position Throttle 40°C pulse width Injector

Introduction

Engine control unit (ECU)

Motivation

1022.27 904.69

Architecture

860.35 27.84 % 768.75 11.89 ms

Evaluation

Conclusion

8

Contributions: CarMA CARMA: A smartphone-based, make and model-independent platform providing programming abstractions for scanning and tuning

Wireless connectivity

On-Board Sensing

Programmability

Fosters ecosystem of car modifications Introduction

Motivation

Architecture

Evaluation

Conclusion

9

Contributions: Sample Apps Implementation of sample apps that allow non-expert users to personalize and automatically optimize cars for different drivers and/or route conditions

Improve responsiveness for hilly route

Introduction

Maximize fuel efficiency

Motivation

Support user diversity

Architecture

Evaluation

Enforce safer driving behavior

Conclusion

10

Contributions: Benefits of Personalized Tuning

A demonstration of personalized tuning that can exploit extrinsic variability to achieve significant fuel efficiency or responsiveness gains

Introduction

Motivation

Architecture

Evaluation

Conclusion

11

CARMA Architecture

Introduction

Motivation

Architecture

Evaluation

Conclusion

12

Scanning Subsystem 1

2

6

3 CARMA

4 5 Protocol Vehicle Response: 0768006A Vehicle 48 Speed 6B0110 Sensor 41 0D 28 = 40 km/h Request: 05 vehicle speed F1 sensor 0D Optimizations Heterogeneity

Introduction

Motivation

Architecture

Interface Heterogeneity

Evaluation

Conclusion

13

Tuning Subsystem setRPMLimit(); commit();

1

2 CARMA

3

5

prepare();

4

Reverse OBD-II Engineering interface

Introduction

Motivation

Download routine

Level of Abstraction ECU firmware

ECU memory

Architecture

Evaluation

Conclusion

14

Tuning Subsystem: ModAPI Mod

Response

Economy

Safety

DisableEGR





EnrichMixture





IncreaseSparkTiming





AdjustShiftDownPoints







LimitRPM







DecreaseShiftTime



Client code

CARMA code

tuner = ATuner.Stub.asInterface(service); tuner.loadCurrentSettings() tuner.applyMod(ModNames.LimitRPM, rpmVal) tuner.commitChanges()

Introduction

Motivation

new TableSetMod( ECUTableName.Disable_All_Injectors_High_MPH, 0, 0, 0, 2, 255), new TableSetMod( ECUTableName.Disable_All_Injectors_High_MPH, 1, 1, 0, 2, limit + 1), new TableSetMod( ECUTableName.Disable_1_Injector_High_MPH, limit), new TableSetMod( ECUTableName.Disable_2_Injectors_High_MPH, limit)

Architecture

Evaluation

Conclusion

15

Evaluation Goals

1

Does CarMA raise the level of abstraction? Implementation of sample applications Micro-benchmarks 



2

Does CarMA provide significant fuel efficiency gains? Test runs using route-specific fuel efficiency optimizations on five different routes Comparison of the recorded sensor data from baseline and modified runs 



Introduction

Motivation

Architecture

Evaluation

Conclusion

16

Evaluation: Applications

98 LOC

Scan App

214 LOC

Tune Wizard

408 LOC

Route Evaluator

60 LOC

Valet Mode Introduction

Motivation

Architecture

76 LOC

Driver Customizer Evaluation

Conclusion

17

Evaluation: Tune Wizard

Alice

Enable EGR Increase torque timing Limit RPM to 5000 Limit RPM to 3000 Introduction

Motivation

Architecture

Evaluation

Conclusion

18

Evaluation: Fuel Efficiency Gains Speed limit Spee d

3

Traffic lights

Recorded data for baseline runs and runs Elevation using modifications gain

2 1

Traffic lights

Elevation gain

Experimented with multiple drivers

0

Conges tion

Grade

Congestion Introduction

Motivation

Max. grade Architecture

Recorded data for more than 1100 miles of driving Evaluation

Conclusion

19

Experimental Results: Fuel Economy Fuel economy for one driver

Fuel economy improved by 11% on average Would save more than $18B in the US annually Trip

Introduction

Motivation

Architecture

Evaluation

Conclusion

20

Experimental Results: Validating Applications RPM vs. throttle pos. for DriverCustomizer

Aggressive driving behavior is prevented

Introduction

Motivation

Architecture

Evaluation

Conclusion

21

Related Work Sensing

Torque

eco:Drive

Powr Tuner

CARMA Firmware Upgrade

Mechanics

Control Introduction

Motivation

GreenGPS

Analysis Architecture

Evaluation

Conclusion

22

Conclusions CarMA provides programming abstractions for scanning and tuning automobiles via mobile devices

Usable by non-experts for personalized tuning

CarMA apps can achieve significant fuel efficiency gains by inhibiting aggressive driving behavior and enforcing limits

Introduction

Motivation

Architecture

Evaluation

Conclusion

23

Future Work Extending CarMA for a broader range of makes and models

Adding safety mechanisms to prevent accidental or malicious damage to vehicles using CarMA

Introduction

Motivation

Architecture

Evaluation

Conclusion

24

CARMA: Towards Personalized Automotive Tuning Tobias Flach1, Nilesh Mishra1, Luis Pedrosa1, Christopher Riesz2, Ramesh Govindan1 1 University

of Southern California 2 Rutgers University, Camden Campus

Sensys 2011

Improving the State of the Art Expressivity

CARMA

Specialized tuning software Fuel economy / Performance modes Complexity

Introduction

Motivation

Architecture

Evaluation

Conclusion

26

Security Considerations Implemented functionality  Checks for conflicting modifications  Definition of safe value ranges for parameters Additional ideas  Application certification  Mandatory "kill switch" Value range (Desired Idle RPM; single cell)

0

500

1200

2500

1700

Safe range

Introduction

Motivation

Architecture

Evaluation

Conclusion

27

Experimental Results: Economy variability Fuel economy for different drivers

Impact of mods depends on “old” driving behavior

Introduction

Motivation

Architecture

Evaluation

Conclusion

28

Experimental results: Speed and RPM limits Speed on trip 3

RPM CDF for trip 4B

Speed limit is enforced Introduction

Motivation

Architecture

RPM long tail is cut Evaluation

Conclusion

29

Background: Scanning & Tuning

Introduction

Motivation

Architecture

Evaluation

Conclusion

30

OBD-II Port

Introduction

Motivation

Architecture

Evaluation

Conclusion

31

Suggest Documents