Fault Detection and Isolation for Lithium-Ion Battery System Using Structural Analysis and Sequential Residual Generation

2014 ◽  
Author(s):  
Zhentong Liu ◽  
Qadeer Ahmed ◽  
Giorgio Rizzoni ◽  
Hongwen He
Keyword(s):  
Structural Analysis ◽  
Fault Detection ◽  
Cooling System ◽  
Hazard Analysis ◽  
Lithium Ion ◽  
Test Construction ◽  
Fault Isolation ◽  
Fault Detection And Isolation ◽  
Battery Cell ◽  
Battery Systems

This paper presents a systematic methodology based on structural analysis and sequential residual generators to design a Fault Detection and Isolation (FDI) scheme for nonlinear battery systems. The faults to be diagnosed are highlighted using a detailed hazard analysis conducted for battery systems. The developed methodology includes four steps: candidate residual generators generation, residual generators selection, diagnostic test construction and fault isolation. State transformation is employed to make the residuals realizable. The simulation results show that the proposed FDI scheme successfully detects and isolates the faults injected in the battery cell with cooling system at different times. In addition, there are no false or missed detections of the faults.

scholarly journals Estimation and Fault Diagnosis of Lithium-Ion Batteries: A Fractional-Order System Approach

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Shulan Kong ◽  
Mehrdad Saif ◽  
Guozeng Cui
Keyword(s):  
Fault Diagnosis ◽  
Fault Detection ◽  
Fractional Order ◽  
Sliding Mode ◽  
Estimation Error ◽  
Lithium Ion ◽  
Fault Isolation ◽  
Sliding Mode Observer ◽  
Fault Detection And Isolation ◽  
Order System

This study investigates estimation and fault diagnosis of fractional-order Lithium-ion battery system. Two simple and common types of observers are designed to address the design of fault diagnosis and estimation for the fractional-order systems. Fractional-order Luenberger observers are employed to generate residuals which are then used to investigate the feasibility of model based fault detection and isolation. Once a fault is detected and isolated, a fractional-order sliding mode observer is constructed to provide an estimate of the isolated fault. The paper presents some theoretical results for designing stable observers and fault estimators. In particular, the notion of stability in the sense of Mittag-Leffler is first introduced to discuss the state estimation error dynamics. Overall, the design of the Luenberger observer as well as the sliding mode observer can accomplish fault detection, fault isolation, and estimation. The effectiveness of the proposed strategy on a three-cell battery string system is demonstrated.

scholarly journals Structural Analysis Based Fault Detection and Isolation Applied for A Lithium-Ion Battery Pack

2015 ◽  
Vol 48 (21) ◽  
pp. 1465-1470 ◽  
Author(s):  
Zhentong Liu ◽  
Hongwen He ◽  
Qadeer Ahmed ◽  
Giorgio Rizzoni
Keyword(s):  
Structural Analysis ◽  
Fault Detection ◽  
Lithium Ion Battery ◽  
Lithium Ion ◽  
Fault Detection And Isolation ◽  
Battery Pack

Multi-Fault Detection and Isolation for Lithium-Ion Battery Systems

2021 ◽  
pp. 1-1
Author(s):  
Kai Zhang ◽  
Xiaosong Hu ◽  
Yonggang Liu ◽  
Xianke Lin ◽  
Wenxue Liu
Keyword(s):  
Fault Detection ◽  
Lithium Ion Battery ◽  
Lithium Ion ◽  
Fault Detection And Isolation ◽  
Battery Systems

Multiple faults detection and isolation approach applied to a kraft recovery boiler

TAPPI Journal ◽  
2014 ◽  
Vol 13 (1) ◽  
pp. 33-41
Author(s):  
YVON THARRAULT ◽  
MOULOUD AMAZOUZ
Keyword(s):  
Fault Detection ◽  
Early Detection ◽  
False Alarm ◽  
False Alarm Rate ◽  
Principal Component ◽  
Fault Isolation ◽  
Fault Detection And Isolation ◽  
Detection Scheme ◽  
Multiple Faults ◽  
Recovery Boiler

Recovery boilers play a key role in chemical pulp mills. Early detection of defects, such as water leaks, in a recovery boiler is critical to the prevention of explosions, which can occur when water reaches the molten smelt bed of the boiler. Early detection is difficult to achieve because of the complexity and the multitude of recovery boiler operating parameters. Multiple faults can occur in multiple components of the boiler simultaneously, and an efficient and robust fault isolation method is needed. In this paper, we present a new fault detection and isolation scheme for multiple faults. The proposed approach is based on principal component analysis (PCA), a popular fault detection technique. For fault detection, the Mahalanobis distance with an exponentially weighted moving average filter to reduce the false alarm rate is used. This filter is used to adapt the sensitivity of the fault detection scheme versus false alarm rate. For fault isolation, the reconstruction-based contribution is used. To avoid a combinatorial excess of faulty scenarios related to multiple faults, an iterative approach is used. This new method was validated using real data from a pulp and paper mill in Canada. The results demonstrate that the proposed method can effectively detect sensor faults and water leakage.

Image-Based Versus Signal-Based Sensors for Machine Fault Detection and Isolation

2014 ◽  
Author(s):  
Heshan Fernando ◽  
Vedang Chauhan ◽  
Brian Surgenor
Keyword(s):  
Fault Detection ◽  
High Speed ◽  
Fault Isolation ◽  
Video Data ◽  
Fault Detection And Isolation ◽  
Single Camera ◽  
Multiple Faults ◽  
Multiple Sensors ◽  
Machine Fault ◽  
And Performance

This paper presents the results of a comparative study that investigated the use of image-based and signal-based sensors for fault detection and fault isolation of visually-cued faults on an automated assembly machine. The machine assembles 8 mm circular parts, from a bulk-supply, onto continuously moving carriers at a rate of over 100 assemblies per minute. Common faults on the machine include part jams and ejected parts that occur at different locations on the machine. Two sensor systems are installed on the machine for detecting and isolating these faults: an image-based system consisting of a single camera and a signal-based sensor system consisting of multiple greyscale sensors and limit switches. The requirements and performance of both systems are compared for detecting six faults on the assembly machine. It is found that both methods are able to effectively detect the faults but they differ greatly in terms of cost, ease of implementation, detection time and fault isolation capability. The conventional signal-based sensors are low in cost, simple to implement and require little computing power, but the installation is intrusive to the machine and readings from multiple sensors are required for faster fault detection and isolation. The more sophisticated image-based system requires an expensive, high-resolution, high-speed camera and significantly more processing power to detect the same faults; however, the system is not intrusive to the machine, fault isolation becomes a simpler problem with video data, and the single camera is able to detect multiple faults in its field of view.

Nonlinear Fault Detection and Isolation for a Lithium-Ion Battery Management System

2010 ◽  
Author(s):  
Jim Marcicki ◽  
Simona Onori ◽  
Giorgio Rizzoni
Keyword(s):  
Fault Detection ◽  
Hybrid Electric Vehicle ◽  
Sliding Mode ◽  
Estimation Error ◽  
Lithium Ion ◽  
Open Loop ◽  
Operating Conditions ◽  
Fault Detection And Isolation ◽  
Battery Management System ◽  
Loop Model

Lithium-ion batteries are a growing source for electric power, but must be maintained within acceptable operating conditions to ensure efficiency and reliability. Therefore, a robust fault detection and isolation scheme is required that is sensitive enough to determine when sensor or actuator faults present a threat to the health of the battery. A scheme suitable for a hybrid electric vehicle battery application is presented in this work. The diagnostic problem is formulated as a nonlinear parity equation approach, but is modified for the considered application. Sliding mode observers are designed for input estimation, while the output voltage estimation is performed using an open loop model. The selection of optimal thresholds given a maximum allowable probability of error is also considered. An assessment of the design using real-world driving-cycle data leads to the conclusion that the estimation error of the observers determines a lower bound on the minimum detectable fault magnitude.

scholarly journals Water Condensation in Traction Battery Systems

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 1171
Author(s):  
Woong-Ki Kim ◽  
Fabian Steger ◽  
Bhavya Kotak ◽  
Peter Knudsen ◽  
Uwe Girgsdies ◽  
...  
Keyword(s):  
Cooling System ◽  
Lithium Ion ◽  
Internal Surface ◽  
Normal Operation ◽  
Battery System ◽  
Water Condensation ◽  
Battery Systems ◽  
Gradient Based ◽  
And Performance ◽  
High Level

Lithium-ion traction battery systems of hybrid and electric vehicles must have a high level of durability and reliability like all other components and systems of a vehicle. Battery systems get heated while in the application. To ensure the desired life span and performance, most systems are equipped with a cooling system. The changing environmental condition in daily use may cause water condensation in the housing of the battery system. In this study, three system designs were investigated, to compare different solutions to deal with pressure differences and condensation: (1) a sealed battery system, (2) an open system and (3) a battery system equipped with a pressure compensation element (PCE). These three designs were tested under two conditions: (a) in normal operation and (b) in a maximum humidity scenario. The amount of the condensation in the housing was determined through a change in relative humidity of air inside the housing. Through PCE and available spacing of the housing, moisture entered into the housing during the cooling process. While applying the test scenarios, the gradient-based drift of the moisture into the housing contributed maximum towards the condensation. Condensation occurred on the internal surface for all the three design variants.

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