Gm Global Technolgoy Operations, Inc.

Other

Delphi Technologies, Inc.

Delco Electronics Corporation

Yuen-Kwok Chin

William C Lin

Youssef A Ghoneim

Jihua Huang

Weiwen Deng

David M Sidlosky

Hsien Heng Chen

Yilu Zhang

Mutasim Abdurrahman Salman

Xiaodong Zhang

Yong Han Lee

William Chin-Woei Lin

Stephen R Pastor

Edward John Bedner

Michael Douglas Rizzo

Ronald Paul

David S Rule

Alan L Browne

Shih-Ken Chen

Xidong Tang

Steven W Holland

Michael Paul Turski

Douglass L Carson

Duane Edward Bassett

Ansaf Ibrahem Alrabady

Kwang-Keun Shin

Balarama Vempaty Murty

Mark N Howell

Pulak Bandyopadhyay

Sanket S Amberkar

Soumen De

Rami I Debouk

Alan J Lee

Howard Hans Ludwig

Jing Zhang

Hong Xing Hu

Edmund Stanley Browalski

Vivek Jaikamal

Sabyasachi Bhattacharya

Debprakash Patnaik

Bakhtiar Brian Litkouhi

Brian James Koch

Kevin Austin O'Dea

Ashok Chandy

Damon R Frisch

Chih-Hung Yen

Alexander Kade

Mark T Riefe

Jenne-Tai Wang

Aleksander Boguslaw Hac

John F Hoying

Mark Philip Colosky

Jian Lin

Jeffery Alan Zuraski

David John Barta

Steven L Tracht

Kathryn L Pattok

Scott P Sherman

Philip Mark Headley

Paul A Grougan

Eldon Gerrald Leaphart

Rahul G Chougule

Prakash K Kulkarni

Phanu Amatyakul

Sugato Chakrabarty

Scott D Morrison

Cheng-Foo Chen

Andrea M Simon

George Paul Montgomery, Jr

Eugene A Rodden

Joachim Busshardt

Rowland Curl Augustus

Sean Padraig O'Connell

John P Whaite, Jr

Manxue Lu

David P Lynch

A method is provided for determining a state-of-health of a battery in a vehicle-during an engine cranking phase. An engine cranking phase is initiated. Characteristic data is recorded that includes battery voltage data and engine cranking speed data during the engine cranking phase. The characteristic data is provided to a pre-processing unit. The pre-processing unit normalizes the characteristic data for processing within a classifier. The normalized data is input o the classifier for determining the vehicle battery state-of-health. The classifier has a trained state-of-health decision boundary resulting from a plurality of trials in which predetermined characterization data is collected with known classes. The battery state-of-health is classified based on the trained state-of-health decision boundary.

Pattern recognition approach to battery diagnosis and prognosis

A method to assist steering of a vehicle equipped with an active steering system when operating in a reverse direction is provided. The method comprises monitoring vehicle operating characteristics and an operator steering input. Boundaries of a target region and a reference point are determined. A target steering angle range is calculated based upon the reference point and the target location. A controlled steering angle of the active steering system is corrected when the operator steering input is outside the target steering angle range. An aspect of the invention included determining the reference point comprising a point of intersection of a first vector and a second vector, the first vector parallel to and passing through a centerline of a rear axle of the vehicle and the second vector perpendicular to and passing through a centerline of an inside front steerable wheel of the vehicle.

Method and system for vehicle parking assistance

An adaptive vehicle control system that classifies a drivers driving style based on vehicle headway control. The system reads sensor signals to identify the range and range rate between a subject vehicle and a preceding vehicle, where the range rate is close to zero if the distance between the subject vehicle and the preceding vehicle is relatively steady, the range rate is negative when the subject vehicle is closing in on the preceding vehicle and the range rate is positive when the subject vehicle is falling behind the preceding vehicle. The range rate, the subject vehicle speed and other signals are used to classify the drivers driving style based on how fast the subject vehicle closes in on the preceding vehicle or falls behind, and the following distance between the subject vehicle and the preceding vehicle. The system can then classify the headway-control maneuver using selected discriminant features.

Adaptive vehicle control system with driving style recognition based on headway distance

A vehicle control system that classifies a driver's driving style based on characteristic maneuvers. The system includes a plurality of vehicle sensors that detect various vehicle parameters. A maneuver identification processor receives the sensor signals to identify a characteristic maneuver of the vehicle and provides a maneuver identifier signal of the maneuver. A style characterization processor receives the maneuver identifier signals, sensor signals from the vehicle sensors and the traffic and road condition signals, and classifies driving style based on the signals to classify the style of the driver driving the vehicle. The classification of the driver style can be provided for a level-1 combination that combines the classification results from different maneuver type classifiers for a single maneuver, a level-2 combination that combines the classification results from multiple maneuvers that are of the same type and a level-3 combination that combines the classification results from different types of characteristic maneuvers.

Adaptive vehicle control system with integrated maneuver-based driving style recognition

An adaptive vehicle control system that classifies a driver's driving style based on characteristic curve-handling maneuvers and road and traffic conditions. The system includes a plurality of vehicle sensors that detect various vehicle parameters. A maneuver identification processor receives the sensor signals to identify a characteristic maneuver of the vehicle and provides a maneuver identifier signal of the maneuver. The system also includes a traffic and road condition recognition processor that receives the sensor signals, and provides traffic condition signals identifying traffic conditions and road condition signals identifying road conditions. A style characterization processor receives the maneuver identifier signals, sensor signals from the vehicle sensors and the traffic and road condition signals, and classifies driving style based on the signals to classify the style of the driver driving the vehicle.

Adaptive vehicle control system with driving style recognition

An adaptive vehicle control system that classifies a drivers driving style based on highway on/off ramp maneuvers. Once the maneuver has been determined to be an on-ramp maneuver or an off-ramp maneuver, a style characterization processor can classify the maneuver using selected discriminant features obtained or derived from the maneuver.

Adaptive vehicle control system with driving style recognition based on maneuvers at highway on/off ramps

A system and method for providing autonomous and remote vehicle maintenance and repair. The system employs an on-board diagnosis and prognosis module that monitors one or more vehicle buses to identify trouble codes and other information indicating a vehicle problem. The on-board module causes a telematic device on the vehicle to broadcast a message including a problem code that identifies the problem the vehicle is having. A remote repair center may receive the message and may identify a software upgrade patch associated with the problem that can be transmitted to the vehicle to upgrade its software to correct the problem. Also, the message may be received by another vehicle that is part of a broadcast network that has previously received the software upgrade patch to fix a problem on that vehicle, where the receiving vehicle may transmit the software upgrade patch to the vehicle having the problem.

Autonomous vehicle maintenance and repair system

An adaptive vehicle control system that classifies a drivers driving style based on vehicle launching maneuvers. A process determines whether the vehicle speed signal during a predetermined time window is greater than a speed threshold, whether the vehicle speed signal before the time window is less than the speed threshold and whether the average of the vehicle longitudinal acceleration during the time window is greater than a first longitudinal acceleration threshold and, if so, determines if the vehicle is in a vehicle launching maneuver. The process then determines that the vehicle launching maneuver has ended if the average of the vehicle longitudinal acceleration during a second time window is less than the longitudinal acceleration threshold. The style characterization processor can then classify the vehicle launching maneuver using selected discriminant features.

Adaptive vehicle control system with driving style recognition based on vehicle launching

An integrated diagnosis and prognosis system that collects vehicle information over the life of a vehicle and its development. The system provides the collected vehicle information to supplier management, product development management, service/dealership management, customer relations departments and production facilities, which use the information to take certain action for existing vehicles, fleets of vehicles or future vehicles to improve vehicle reliability and quality.

Integrated diagnosis and prognosis system as part of the corporate value chain

A system that classifies driver driving skill based on on-ramp or off-ramp maneuvers. The system reads sensor signals for vehicle speed and vehicle yaw rate. The system determines that the vehicle has made an on-ramp or off-ramp maneuver using the vehicle speed signal and the yaw-rate signal and then classifies the driver's driving skill using selected discriminant features obtained or derived from the on-ramp or off-ramp maneuver.

Vehicle stability enhancement control adaptation to driving skill based on highway on/off ramp maneuver

A system and method for enhancing vehicle diagnostic and prognostic algorithms and improving vehicle maintenance practices. The method includes collecting data from vehicle components, sub-systems and systems, and storing the collected data in a database. The collected and stored data can be from multiple sources for similar vehicles or similar components and can include various types of trouble codes and labor codes as well as other information, such as operational data and physics of failure data, which are fused together. The method generates classes for different vehicle components, sub-systems and systems, and builds feature extractors for each class using data mining techniques of the data stored in the database. The method also generates classifiers that classify the features for each class. The feature extractors and feature classifiers are used to determine when a fault condition has occurred for a vehicle component, sub-system or system.

Aggregated information fusion for enhanced diagnostics, prognostics and maintenance practices of vehicles

An embodiment contemplates a method for estimating a capacity of a battery. A state of charge is determined at a first instant of time and at a second instant of time. A difference in the state of charge is determined between the first instant of time and the second instant of time. A net coulomb flow is calculated between the first instant of time and the second instant of time. The battery capacity is determined as a function of the change in the state of charge and the net coulomb flow.

Method for battery capacity estimation

An adaptive vehicle control system that classifies a driver's driving style based on vehicle passing maneuvers. A process determines whether the vehicle has started a lane change from a first lane to a second lane as a first phase of the passing maneuver. If so, the process determines whether the lane change to the second lane has been completed as a second phase of the passing maneuver. If the lane change to the second lane has been completed, the process determines whether there has been a lane change back to the first lane to complete the passing maneuver as a third phase of the passing maneuver. Further, the process determines whether a time threshold has been exceeded after the passing maneuver is in a second phase, but no lane change back to the first lane has occurred.

Adaptive vehicle control system with driving style recognition based on vehicle passing maneuvers

An adaptive control VGR steering system that varies the steering gear ratio between a vehicle hand-wheel angle and the road wheel angle based on vehicle speed and one or more of hand-wheel angle, driver attentiveness and a driver's driving style and skill.

Control adaptation of variable gear ratio steering

A vehicle stability enhancement system that is adapted for an estimated driver workload. The system includes a driver workload estimation processor that estimates the driver workload based on certain factors, such as the vehicle speed or driver-behavior factors. The driver workload estimation is used to adjust the damping ratio and natural frequency in dynamic filters in a command interpreter to adjust a desired yaw rate signal and a desired side-slip signal. The driver workload estimation is also used to generate a yaw rate multiplication factor and a side-slip multiplication factor that modify a yaw rate stability signal and a side-slip stability signal in a feedback control processor that generates a stability control signal.

Driver workload-based vehicle stability enhancement system

Growing community of inventors

Troy, MI, United States of America

Yuen-Kwok Chin