Automotive Control Solutions

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Transcript Automotive Control Solutions

Automotive Control Solutions Russell Potter – CTO, President Alex Gutica - CFO Brian Nelson - CTO

Automotive Control Solutions

The AF Optimizer - An ENSC440 project -

Contents

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The ACS Team     The AF Optimizer The 440 project In-car Demo Now The future Conclusion Questions?

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Automotive Control Solutions

 A cutting-edge development team  specialize in control of automotive performance through electronic air/fuel optimization  Appeal to owners of any car, particularly older vehicles with simple electronic control 3

Who Are We?

 User Interface Firmware Lead  Russell Potter  DSP Firmware Lead  Alex Gutica  Hardware Lead  Brian Nelson 4

Internal Combustion Engine

   Requires a correct mixture of fuel and air in order to function Fuel is mixed with the air, compressed, and ignited. When ignited, the air/fuel mixture drives pistons down, which turns a crankshaft.

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Fuel Delivery

   The most efficient burn mixture has an 14.7:1 air-fuel ratio.

The lean condition   The air-fuel ratio is too high Results in detonation, power loss, increased emissions The rich condition   The air-fuel ratio is too low Results in reduced economy, increased emissions, power loss 6

Fuel Injection System

Proper fuel delivery is electronically controlled through a fuel injection and ignition timing system 7

 Based on a 2 variable present map in the ECU   Load/Airflow meter RPM

Fuel Delivery

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The Problem

 Fuel maps and fuel delivery are designed for compromise  By modifying fuel delivery and consequently air fuel ratios, improvements can be made  Performance  Economy  Improved Emissions 9

Why Modify an Already “Tuned” System?

 Are the original engineers incompetent?

 No but, the original characteristics of the motor can be changed  Performance enhancements  Changing the amount of air\fuel flowing into the motor  General engine wear  Perhaps a different “compromise” is desired 10

Current Solutions for Modifying Air Fuel Ratios

    Modifying the computer: new fuel maps    Model-specific Costly Lack of user-specific ability to tune Standalone systems  Complete computer replacement is very intrusive  Requires extensive, expensive tuning Mechanical solutions  Rudimentary APEXi SAFC  Our direct competition 11

The AF Optimizer

 Its functionality and potential market  Its competitive edge  Features  System Design and Implementation  Hardware and firmware 12

The AF Optimizer

 What does it do?

   Recalibrates air flow sensor data, while monitoring car Allows for flexible tuning of air fuel ratios  Moves to different location on original fuel map Monitors automobile sensors with real-time visual display to users  Why would one buy it?

 To inexpensively and safely optimize delivery of fuel to their engine 13

Target Market

 Customer needs to tune their fuel system  Desires better performance  Wants a simple, noninvasive install  29 Billion Dollar aftermarket part industry  Our target demographic is young people  With older cars  Who demand an inexpensive, feature packed fuel control system 14

Compatibility

 Compatible with wide range of manufacturers  Required:  Fuel injection  MAP or VAF sensor  0-5V Scale  Reality: Older, simple computer is better 15

AF Optimizer Advantages

 First and foremost, price  Versatile for use on many different vehicles  Easy to install and remove  Un-intrusive to the vehicle  Real-time monitoring  Works on older cars 16

Feature Overview

 Airflow tuning features  Shift Light Features  Monitoring Features 17

Tuning Features

 Many Tuning points provides more tunability  based on RPM and Throttle %  RPM Tuning  2000-8750 RPM - 250 RPM increments  75% to 125% - 1% increments  Linearly Interpolates between tuning points 3000 3250 3500 3750 >102% 110% 109% 107% 98% 100% 97% 98% 18

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Tuning Features

 Throttle Percentage Tuning  2 Calibration Curves: High / Low Throttle  User defined - based on throttle % thresholds  Throttle Thresholds  Low: e.g. <30% throttle  High: e.g. >90% throttle  Linearly interpolates between the thresholds 20

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Tuning Features

 Overall: 2-Dimensional interpolation  RPM and Throttle % are variables 22

Shift Light Features

 2000-10000 RPM in 100 RPM increments    5 Sequentially lit LEDs LEDs light up every 100 RPM as you approach your desired shift point Increasing brightness  Example where shift light set to 5000 RPM 23

Monitoring Features

  Real-time monitoring of engine’s sensors  RPM  Throttle %  Battery Voltage RPM: 3250rpm Throttle: 80% Battery: 14V O2 Sensor: 220mV  O 2 Sensor Voltage Airflow and calibration monitoring  Calibration %  Pre and Post Airflow Voltages Airflow: 106% Pre: 2050mV Post: 2184mV 24

RPM Sensor Throttle Sensor

System Overview

ECU Airflow Sensor AF Optimizer

Component and System Layout

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AF Optimizer: Hardware

 Part Sourcing  PIC 16F Microcontroller  Maxim 10-bit DAC  Noritake 4-line x 20 character VFD  5Volt Regulator  Input Circuitry 26

Hardware Challenges

 PIC Microcontroller  Need to service the display, inputs and DAC fast  Fast speed for calculations  DAC Accuracy  Power Management  I/O conditioning  Noisy car signals, voltage scaling  Creating a stable, fast analog output with DAC 27

AF Optimizer: Firmware

  Performed two functions  Sample inputs, calculate, output  Handle interaction with user   Buttons Display Written in C    High level functionality Easy writing, debugging Memory & Processor Usage 28

Firmware Challenges

  Debugging and Simulation   Simulator has limited functionality PIC was new to us Timing    We had strict timing demands Needed all three hardware timers Required very careful time management 29

Final Product Performance 1

  Successful integration into the vehicle was dependent upon system response speed Response to a 16Hz sine as airflow input (unrealistic, but illustrates system performance) 30

Final Product Performance 2

   A more realistic response to a square wave 1.5 ms system delay Small capacitor used to eliminate discontinuities 31

Integration Challenges

   Very smooth integrating into the car    Research of sensor signals In-car signal testing with oscilloscope Great lab setup for proper simulation Start up and Connection issues   Starter draws current and dropped the battery voltage  FIX: Cap and diode Bad connections with breadboard and car wiring  FIX: Soldered car wiring harness & PCB Car has a bad O 2 Sensor 32

Demo Time

 Things to demonstrate:  Monitoring  How to setup throttle values  Shift light  How to set airflow calibrations  Car running and driving  Out to B-LOT everyone 33

Dyno Results

 Very Impressive Results!!

 Running too rich loses power.

 Running too lean loses power…  We are able to change the air fuel ratios  Here are the results 34

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Baseline Run

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Rich Run

 Tried 120% but threw Check Engine Light  Tuned to 110% from 2000-6700 RPM (redline)  Results: 37

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Rich Run

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Lean Run

 Running too lean lost power in low RPMs  Original ECU runs too rich at high RPMs  Use AF Optimizer to lean high RPMs  Results: 40

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Engineering Considerations

  Positive system feedback due to vehicle velocity  Does not affect airflow into engine  Dynamometer is appropriate for vehicle tuning System memory considerations (derivatives)  Precautions were taken to prevent derivative reversal    Airflow signal adjustability range limited to 75% - 125% High and low throttle curves at least 20% of entire throttle range apart Testing indicates airflow signal changes much faster than throttle 43

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Budget

 Proposed Budget:  Actual Spending:  Difference: $665 $200 $-465  Summary We

UNDERSPENT!

Due to building only 1 prototype, cheap dyno time 45

AF Optimizer: Schedule

Predicted Completion Dates

Firmware:

February 27

Hardware: System Integration:

March 13

Final Testing:

March 6 March 24 Actual Completion Dates March 15 March 6 March 17 April 4

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AF Optimizer: Now

 Have a fully functional prototype!

 We’ve priced many parts in quantities  The display dominates  Accounts for as much cost as all others combined  Produced prototype PCB and casing  Plans underway for production model  Designed to use 1 PIC for cost 47

AF Optimizer: The Future

 Small distribution at first  Use online car clubs for marketing  Will hopefully get feedback  If all goes well, incorporate!

 Outsource manufacture to overseas  Build relationships with distributors  Maybe make a few $$ 48

Future Design Considerations

 Split it up into modules  Display and buttons  Main PC Board and wiring to car’s wiring  Shift light (remotely mounted)  Optimize PCB designs 49

ACS Team Summary

 This was a great learning experience  Conclusions  Acknowledgements 50

Lessons Learned

 Time and hard work invested early pays off  Research allows for easier problem solving  Documentation is important for complicated projects 51

Conclusions

 We chose a great project  Because we love cars  It was complex, but workable  We honed our skills learned in 4 years  This product can make money 52

Acknowledgements

 Scott, Lucky, Fred  Dave Atchison, for experience with PIC and Dyno time  ESSEF funding 53

Questions?

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