Gm Global Technolgoy Operations, Inc.

Xidong Tang

Mutasim Abdurrahman Salman

Yilu Zhang

Brian James Koch

Jian Lin

Xiaodong Zhang

Damon R Frisch

Mark N Howell

Kwang-Keun Shin

Yuen-Kwok Chin

Nick S Kapsokavathis

David W Walters

Pulak Bandyopadhyay

Steven W Holland

Soumen De

Xiaofeng Mao

Michael J Gielniak

Satish Rajagopalan

Hong S Bae

Joseph M Lograsso

Rezina S Nabi

Fan Bai

Mark William Verbrugge

Xinyu Du

Ansaf Ibrahem Alrabady

Yiran Hu

Andrew J Namou

Balarama Vempaty Murty

Robert Charles Baraszu

Satnam Singh

Andrew C Baughman

Rami I Debouk

Wei Liu

Yandong Zhang

Walter A Dorfstatter

Monika A Minarcin

Rahul G Chougule

Sugato Chakrabarty

Sabyasachi Bhattacharya

Debprakash Patnaik

George Paul Montgomery, Jr

Youseff A Ghoneim

Steven A Patterson

A system and method for estimating internal parameters of a lithium-ion battery to provide a reliable battery state-of-charge estimate. The method uses a two RC-pair equivalent battery circuit model to estimate the battery parameters, including a battery open circuit voltage, an ohmic resistance, a double layer capacitance, a charge transfer resistance, a diffusion resistance and a diffusion capacitance. The method further uses the equivalent circuit model to provide a difference equation from which the battery parameters are adapted, and calculates the battery parameters from the difference equation.

Adaptive battery parameter extraction and SOC estimation for lithium-ion battery

A system and method for estimating parameters of a rechargeable energy storage system during a plug-in charge mode include reading a first measured voltage and a measured current from the rechargeable energy storage system while charging the rechargeable energy storage system during a plug-in charge mode, interrupting the charge to stop current flow to the rechargeable energy storage system for a predetermined period of time, reading a second measured voltage during the charge interrupt, calculating a resistance based on the first measured voltage, the second measured voltage and the measured current, calculating an open circuit voltage of the rechargeable energy storage system based on the resistance, the second measured voltage, the measured current and determining the state-of-charge for the rechargeable energy storage system using the open circuit voltage.

Apparatus of SOC estimation during plug-in charge mode

A method includes collecting vehicle health data from a plurality of vehicles. A peer group is identified among the plurality of vehicles. The collected vehicle health data from the peer group into a collaborative vehicle health model, the collaborative vehicle health model being applicable to a current vehicle to predict a state of at least a component of the current vehicle.

Method and system for predicting vehicle battery health using a collaborative vehicle battery health model

A robust battery state-of-charge observer determines a state-of-charge as function of an open circuit voltage by taking into account battery parameter uncertainties, which are due to battery age, variation, and operating conditions, (e.g. temperature and SOC level). Each of the time-varying battery parameter values are bounded. By utilizing the parameter variation bounds in the design process and constantly minimizing the estimation error covariance matrix, the robust observer achieves enhanced robustness to the variations of battery age, variation, and operating conditions such as temperature and SOC level.

Battery state-of-charge observer

A battery state-of-charge (SOC) estimator uses a robust Hfilter design by taking into account the battery parameter uncertainties, which is due to battery age, variation, and operating conditions such as temperature and SOC level. Each of the time-varying battery parameter values and their variation rates are bounded. By utilizing the parameter variation bounds and parameter variation rate bounds into the design process and minimizing the Hgain from the measured current signal to the estimation error of V, the battery SOC estimator can achieve enhanced robustness to the variations of battery age, variation, and operating conditions that include temperature and SOC level.

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A method is provided for determining a battery capacity for a vehicle battery. Open circuit voltages of a vehicle battery are measured during ignition startups. A battery parameter is estimated for the vehicle battery that is a function of a present open circuit voltage measurement for a present ignition startup, a function of at least one open circuit voltage observation of a previous ignition startup, a function of a current draw integration over a time period from a previous ignition startup event to a present ignition startup event, and a function of an adjustment factor. A battery parameter is determined based on a new battery. The battery capacity is calculated as function of the battery parameter for the vehicle battery and the battery parameter for the new battery.

Method and apparatus for estimating battery capacity of a battery

A method for optimizing performance of a system includes determining, via a controller, a state of health (SOH) for each of a plurality of components of the system, and determining a state of function (SOF) of the system using the SOH of each component. The method includes estimating the remaining useful life (RUL) of the system using the system SOF, selecting a cost-optimal control strategy for the system using a costing model, and dynamically, i.e., in real time, executing the selected strategy to extend the estimated RUL. The method may include comparing the selected cost-optimal strategy to a calibrated performance threshold, and executing the selected strategy only when the selected strategy exceeds the threshold. A system includes first and second components and a controller. The controller dynamically executes the above method with respect to the components, which may be a traction motor and battery in one possible embodiment.

Optimizing system performance using state of health information

A cooperative diagnostic and prognosis system for generating a prognosis of at least one component in a vehicle. An in-vehicle diagnostic unit determines a diagnostic signature of the component each time an occurrence of a condition is triggered and transmits the diagnostic signature to an off-board diagnostic unit. The off-vehicle diagnostic unit determines a SOH of the component and a rate-of-change in the SOH of the component. The off-vehicle diagnostic unit determines whether the rate-of-change in the SOH is greater than a threshold. The off-vehicle diagnostic unit requests additional information from the vehicle in response to the rate-of-change in the SOH being greater than the threshold. The additional information relating to operating parameter data associated with the component. The off-vehicle diagnostic unit receives the requested information and predicts a time-to-failure of the component.

Co-operative on-board and off-board component and system diagnosis and prognosis

A method of determining a state of health of a battery in real time includes estimating a parameter value associated with the state of health of the battery and determining one or more of a terminal voltage, an accumulated charge, a state of charge, and a temperature of the battery. The method further includes determining, via a computing device, a reserve capacity of the battery based at least in part on the estimated parameter value and one or more of the terminal voltage, the accumulated charge, the state of charge, and the temperature of the battery.

Dynamic battery capacity estimation

Methods and systems are provided for characterizing a battery. A property of the battery is measured. A dynamic characteristic of the battery is determined from a second order linear dynamic model.

Method and system for characterizing a battery

A method is provided for enhancing service diagnostics utilizing service repair data of previously serviced vehicles. Service repair data of previously serviced vehicles is obtained from a memory storage device. The service data is compiled into a service diagnostic code dataset and a service labor code dataset. The service diagnostic code dataset and service labor code dataset are categorized into an electronic data table. Respective combinations are formed in the electronic data table. An aggregate count is determined for each respective combination in the electronic data table. Either of a respective diagnostic code or a respective service labor code is identified having a correlation with more than one of either service diagnostic codes or service labor codes. At least one of a service repair procedure used to repair the vehicle or a respective service diagnostic code used to identify the fault is modified in response to analyzing the respective combinations.

Process for service diagnostic and service procedures enhancement

A method of determining a state-of-charge for a battery is provided. A startup state-of-charge of the battery is determined as a function of a present open circuit voltage measurement for a present ignition startup, at least one open circuit voltage observation of a previous ignition startup, and a current draw integration over a time period from a previous ignition startup event to a present ignition startup event. A run state-of-charge change of the battery is determined for an ignition key-on operation. The run state-of-charge change comprises a difference between the present open circuit voltage measurement and the at least one previous open circuit voltage observation, and is determined in response to of a current draw integration over a respective period of time. The state-of-charge of the battery is calculated based on a function of the startup state-of-charge and the run state-of-charge change of the battery.

Method and apparatus for estimating SOC of a battery

A system and method for determining the health of a component includes retrieving measured health signatures from the component, retrieving component usage variables, estimating component health signatures using an aging model, determining an aging derivative using the aging model and calculating an aging error based on the estimated component health signatures, the aging derivative and the measured health signatures.

Method and apparatus for vehicle component health prognosis by integrating aging model, usage information and health signatures

A system and method for providing component and sub-system state of health prognosis in a complex system using fault models and component aging models. The method includes determining a current state of health value for a sub-system using fault signature test results and determining current state of health values for a plurality of components in the sub-system using the fault signature test results. The method also determines current state of health values for components in the system that cannot use fault signature test results using a first probability model and the current state of health values for the plurality of components. The method determines predicted future state of health values for the components in the sub-system using component aging models and determines a predicted future state of health value for the sub-system using a second probability model and the future state of health values of the components.

Health prognosis for complex system using fault modeling

A system and method for use with a vehicle battery pack having a number of individual battery cells, such as a lithium-ion battery commonly used in hybrid electric vehicles. In one embodiment, the method evaluates individual battery cells within a vehicle battery pack in order to obtain accurate estimates regarding their average transient voltage effect, open circuit voltage (OCV) and/or state of charge (SOC) so that a cell balancing process can be performed. These cell evaluations may be performed fairly soon after the vehicle is turned off and in a manner that utilizes a minimal amount of in-vehicle resources.

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Sterling Heights, MI, United States of America

Xidong Tang