AUTOMOTIVE VIRTUAL SENSORSNew Technologies for

WE ARE AT THE ENDOF THE BEGINNING

(John Kelly SVP - Director of IBM Research)

There is a Global Effort to developCOGNITIVE COMPUTING

IBM (IBM.N) said it will invest more than $1 billion to establish a new business unit for WatsonReuters - Thu Jan 9, 2014 2:50am EST

"The biggest thing will be Artificial Intelligence," Schmidt (Google CEO) said at OasisBloomberg - Mar 6, 2014 10:07 PM GMT+0100

China's top search engine Baidu Inc. has hired Google Inc's former Artificial Intelligence (AI) chief Andrew NgReuters - Fri May 16, 2014 4:58pm EDT

COGNITIVE COMPUTING is based onMACHINE LEARNING

tunable modelsadjustedby adapting to given data

MACHINE LEARNING discover INFORMATIONLocked-Up in DATA

WHY THIS IS IMPORTANT FOR YOU

Because we obtained Excellent Resultsby using MACHINE LEARNING to design AUTOMOTIVE VIRTUAL SENSORS:

iTPMS - Tire Pressure Estimator -Speed Estimator - Side Slip Angle Estimator (SSE)

By Leveraging Four Main Skills

Computer Science

Data Science(MACHINE LEARNING)

Domain Knowledge(Engineering)

Embedded SoftwareElectronics

Our Process(AUTOMOTIVE VIRTUAL SENSOR design)

1.Data Collection & Normalization

2.Feature Selection

3.Model Fitting

4.Rapid Prototyping

5.Production Code

1. Data Collection & Normalization(from sensors to DataBase)

1.Data Collection & NormalizationTest Design - Physical Simulators (*) Testing ServicesData Check-In Filtering & Outlier Detection Data Normalization

Server

Job Launcher

Data sender

Workersset

Data

Meta

Algo.

X, Y

Compressedraw data

Jobsqueue/log

Adapter

Algorithms

Adapter

Algorithms

Datapreprocessing

Raw Data

USER

ask_jobjob

ask_data

dataresults

…

RawData

Preprocfunctions

DB

(*) In partnership with

1.Data Collection & NormalizationTest Design - Physical Simulators (*)Testing Services Data Check-InFiltering & Outlier DetectionData Normalization

Test Procedures Wide Range of Sensors and Configurations Installation and Calibration on Vehicles Acquisition Systems Setup

1.Data Collection & NormalizationTest Design - Physical Simulators (*)Testing Services Data Check-InFiltering & Outlier DetectionData Normalization

Real-Time Data Validation to avoid Errors or Shooting

2. Feature Selection(finds the most important variables for the Virtual Sensor)

2. Feature SelectionEngineering Domain Knowledge Features Space ExpansionSpace Dimensionality ReductionSubset Selection

Geometric Corrections Kinetic Corrections

2. Feature SelectionEngineering Domain KnowledgeFeatures Space Expansion Space Dimensionality ReductionSubset Selection

Linear Trasformation Dimensional Analysis

2. Feature SelectionEngineering Domain KnowledgeFeatures Space ExpansionSpace Dimensionality Reduction Subset Selection

Linear Projection Manifold Learning Stochastic Neighbor Embedding

2. Feature SelectionEngineering Domain KnowledgeFeatures Space ExpansionSpace Dimensionality ReductionSubset Selection Recursive Feature Elimination

Wrapper Methods Embedded Methods

3. Model Fitting(here is where the Virtual Sensor Algorithm is made)

3.Model FittingSupport Vector Machines Ensemble MethodsDeep Neural NetworksRecurrent Neural Networks

3.Model FittingSupport Vector MachinesEnsemble Methods Deep Neural NetworksRecurrent Neural Networks

……"tree"t1 tree"tT

category"c category"c

v v fn(v)"> tn

•  feature"vector" "v •  split"func6ons" "fn(v) •  thresholds" "tn •  Classifica6ons "Pn(c)

3.Model FittingSupport Vector MachinesEnsemble MethodsDeep Neural Networks Recurrent Neural Networks

3.Model FittingSupport Vector MachinesEnsemble MethodsDeep Neural NetworksRecurrent Neural Networks

4. Rapid Prototyping

4.Rapid PrototypingVerification and ValidationFast DeploymentSystem Integration Control Loops

User Interfaces

5. Production Code

5.Production CodeResources OptimizationProcessor Specific TuningMulti-Core & Polyhedral OptimizationMicroprocessors and FPGA Targets

Software in-the-loopHardware in-the-loop

APPLICATIONS: NOT JUST AUTOMOTIVEOil & Gas - Aerospace - Automotive

OIL & GAS

AEROSPACE

AUTOMOTIVE APPLICATIONSiTPMS - Tire Pressure Estimator - Speed Estimator - Side Slip Angle Estimator (SSE)

iTPMS(Detect an Under-Inflated Tire)

Do not Require Additional Sensors:Works with CAN Bus Data @ 50 Hz

Continuous Detection in Any Handling Condition

Fully Compliant (*) with:UN ECE-R 64 // FMVSS 138 // Fiat iTPMS PTP

Tire Position Information

(*) Based on available data

Do you REALLY think I will RESET Your TPMS ?

Do you REALLY think I will set the Right Tire Pressure ?

Tire Pressure Estimator(Measure the Tire Pressure)

Do not Require Additional SensorsContinuous Detection in Any Handling ConditionFully Compliant with:

UN ECE-R 64 // FMVSS 138 // Fiat iTPMS PTP (*)

Does Not Requires Calibration // ResetDoes Not Require Continuous GPS CoveragePrecision: 0.1[bar]Rapid Deflation Detection Time: 5[s]Slow Deflation: Calculate Residual Driving Time

(*) Requires Tire Characterization and GPS signal when availableTire Characterization Requires Typically One Day per Tire Set

Speed Estimator - RacingDo Not Require Additional Sensors

Speed Error below 1.0% from 10 to 40 km/h (*)

Speed Error below 0.5% from 40 to 310 km/h (*)

10[ms] Lag Guarantee with proper Data Feed

(*) Requires Either Tire Characterization OR GPS signal when availableTire Characterization Requires Typically One Day per Tire Set

Side Slip Estimator (SSE)Does Not Require Additional Sensors:

Works with CAN Bus Data @ 50 HzDoes Not Require GPSDoes Not Require Tire Characterization (*)Works in ANY Handling Condition

20[ms] Lag GuaranteeMaximum Error: 0.5° RMS up to 45° SSFrom 10 to 300 km/hAvailable for 2WD, 4WD and 4 Wheel Steering

(*) Requires Vehicle CharacterizationVehicle Characterization Requires Typically One Week

WE HAVE A PROCESSto design custom VIRTUAL SENSORS

and deliver production-grade code for Microprocessors or FPGA 

VIRTUAL SENSORdoesn’t mean

SENSORLESS

Moreover

VIRTUAL SENSORScan either

REPLACE existing sensors or

be used to create REDUNDANCY or ADDITIONAL FEATURES 

TPMSAutocalibrationBackup & SafetyEnhanced PrecisionLoad EstimatorRolling Resistance Estimator

Smart TiresEnhanced PrecisionBackup & SafetyLateral Force EstimatorGrip Limit (ABS - Traction)Tire Misuse (Driving Style, Toe-In)Internal Temperature DistributionTread Depth

CUSTOMERS

CERTIFICATIONS

Thank You

Q & A

it.linkedin.com/in/ebusto/

enrico.busto@add-for.com

giuliano.manfredini@mail.leane.it