Trip Specific Worthiness of Replacement of Individual Cells for Battery Pack in Electric Vehicles

2011 ◽  
Author(s):  
Rohit Ugle ◽  
Yaoyu Li
Keyword(s):  
Real Time ◽  
Electric Vehicles ◽  
Battery Pack ◽  
Performance Gain ◽  
Intrinsic Signals ◽  
Battery Packs ◽  
On Line ◽  
The Individual ◽  
And Control ◽  
Battery Module

Ever increasing acceptance of electric vehicles relies on better operation and control of large battery packs. The individual cells in the large battery packs cannot have identical characteristics and may degrade differently due to its manufacturing variability and other factors. It is beneficial to evaluate the performance gain by replacing certain battery modules/cells during actual driving. We have a two-fold objective for this research. First, we are developing an on-line battery module degradation diagnostic scheme using the intrinsic signals of a battery pack equalization circuit. Therefore, a battery “health map” can be constructed and updated in real time. Secondly, based on the derived battery health map, the performance of the battery pack will be evaluated for customer specified trip so as to evaluate the “worthiness of replacing” certain modules/cells.

Adaptive Signal Analysis and Interpretation for Real-time Intelligent Patient Monitoring

1994 ◽  
Vol 33 (01) ◽  
pp. 60-63 ◽  
Author(s):  
E. J. Manders ◽  
D. P. Lindstrom ◽  
B. M. Dawant
Keyword(s):  
Computer Architecture ◽  
Real Time ◽  
Data Abstraction ◽  
Monitoring Strategy ◽  
Intelligent Monitoring ◽  
Patient Status ◽  
On Line ◽  
Main Components ◽  
And Control ◽  
Adaptive Signal

Abstract:On-line intelligent monitoring, diagnosis, and control of dynamic systems such as patients in intensive care units necessitates the context-dependent acquisition, processing, analysis, and interpretation of large amounts of possibly noisy and incomplete data. The dynamic nature of the process also requires a continuous evaluation and adaptation of the monitoring strategy to respond to changes both in the monitored patient and in the monitoring equipment. Moreover, real-time constraints may imply data losses, the importance of which has to be minimized. This paper presents a computer architecture designed to accomplish these tasks. Its main components are a model and a data abstraction module. The model provides the system with a monitoring context related to the patient status. The data abstraction module relies on that information to adapt the monitoring strategy and provide the model with the necessary information. This paper focuses on the data abstraction module and its interaction with the model.

Design of a Magnetic Field-Based Multi Degree-of-Freedom Orientation Sensor Using the Distributed-Multiple-Pole Model

2007 ◽  
Author(s):  
Kok-Meng Lee ◽  
Hungsun Son
Keyword(s):  
Magnetic Field ◽  
Real Time ◽  
Rotating Shaft ◽  
Precision Control ◽  
Real Time Measurement ◽  
Angular Measurements ◽  
Orientation Sensor ◽  
The Individual ◽  
And Control ◽  
Spinning Shaft

Precision control of a tiltable spinning shaft requires real-time measurement of the inclination. Conventional single-axis encoders, though capable of providing high-resolution (linear or angular) measurements, rely on mechanical linkages (that often introduce frictions, backlashes, and singularities) to constrain the device so that the three-DOF motion can be deduced from the individual orthogonal measurements. Vision-based sensors, which have the attractive features of being non-contact, are limited to low speed measurements. We present here an efficient method for designing a magnetic field-based orientation sensor for devices where orientation control of a rotating shaft under the influence of a magnetic field is required. The ability to characterize the magnetic fields and forces in addition to orientation sensing can offer a number of advantages in real-time computation and control.

Real-Time Modeling and Control of Electric Vehicles Charging Processes

2015 ◽  
Vol 6 (3) ◽  
pp. 1375-1385 ◽  
Author(s):  
Guido Benetti ◽  
Maurizio Delfanti ◽  
Tullio Facchinetti ◽  
Davide Falabretti ◽  
Marco Merlo
Keyword(s):  
Real Time ◽  
Electric Vehicles ◽  
Modeling And Control ◽  
Time Modeling ◽  
And Control

Experimental On-Line Frequency Domain Identification and Adaptive Control of a Flexible Slewing Beam

1996 ◽  
Vol 118 (1) ◽  
pp. 58-65 ◽  
Author(s):  
R. I. Milford ◽  
S. F. Asokanthan
Keyword(s):  
Frequency Domain ◽  
Real Time ◽  
Parametric Estimation ◽  
Identification Algorithm ◽  
Function Estimation ◽  
Persistent Excitation ◽  
Domain Identification ◽  
Frequency Domain Identification ◽  
On Line ◽  
And Control

This paper presents experimental results for the real-time adaptive identification and control of a flexible, slewing beam. A frequency domain identification algorithm incorporating non-parametric transfer function estimation and least squares parametric estimation is used to reconstruct an accurate parametric model of the system, capable of accurately tracking changing plant dynamics in real time. This model is subsequently used to produce an LQG compensator which actively damps beam vibration caused by rapid slewing manoeuvres with large payload changes. Non-persistent excitation is addressed in the context of identification during nominal motion. It is shown that after a short duration learning period, the proposed identification scheme will yield a model which is sufficiently accurate for controller synthesis.

scholarly journals Electric Enabler

2017 ◽  
Vol 139 (12) ◽  
pp. 39-39
Author(s):  
John Kosowatz ◽  
Thomas Romer
Keyword(s):  
Production Process ◽  
Lithium Ion Batteries ◽  
Electric Vehicles ◽  
Lithium Ion ◽  
Battery Pack ◽  
Automated System ◽  
Price Point ◽  
Battery Packs ◽  
Full Capacity ◽  
Safety Systems

This article explains how Tesla batteries are making electric vehicles (EVs) affordable for customers. Tesla’s battery revolution began when CEO Elon Musk declared that it would sell a mass-market EV for just $35,000. To produce battery packs cheaply enough to reach that price point, Tesla reengineered not only the production process, but also the factory in which the batteries are made. The Reno, Nev., Gigafactory is not yet operating at full capacity, but it is expected to produce 35 GW per year of lithium-ion batteries, about double the present-day global production. Tesla partnered with Panasonic to revamp the production process, and ended up redesigning the chemistry of the battery itself. The standard “18-650” cell format used thousands of less-expensive commodity cells, similar to lithium-ion batteries used in laptop computers. Tesla replaced individual safety systems built into each cell with an inexpensive fireproof system for the entire battery pack. Now, they have begun producing the new “2170” cell, which delivers higher density through an automated system developed with Panasonic to further reduce costs.

Development of a Two-Dimensional Thermal Model for Li-Ion Battery Pack With Experimental Validation

2019 ◽  
Vol 12 (2) ◽  
Author(s):  
Haoting Wang ◽  
Ning Liu ◽  
Lin Ma
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Experimental Validation ◽  
Computational Cost ◽  
Battery Pack ◽  
Two Dimensional ◽  
Li Ion Battery ◽  
New Approach ◽  
Battery Packs ◽  
Li Ion

Abstract This paper reports the development of a two-dimensional two states (2D2S) model for the analysis of thermal behaviors of Li-ion battery packs and its experimental validation. This development was motivated by the need to fill a niche in our current modeling capabilities: the need to analyze 2D temperature (T) distributions in large-scale battery packs in real time. Past models were predominately developed to either provide detailed T information with high computational cost or provide real-time analysis but only 1D lumped T information. However, the capability to model 2D T field in real time is desirable in many applications ranging from the optimal design of cooling strategies to onboard monitoring and control. Therefore, this work developed a new approach to provide this desired capability. The key innovations in our new approach involved modeling the whole battery pack as a complete thermal-fluid network and at the same time calculating only two states (surface and core T) for each cell. Modeling the whole pack as a complete network captured the interactions between cells and enabled the accurate resolution of the 2D T distribution. Limiting the calculation to only the surface and core T controlled the computational cost at a manageable level and rendered the model suitable for packs at large scale with many cells.

The Impact of Filtering on Sea and Air Operations

1983 ◽  
Vol 36 (1) ◽  
pp. 74-80
Author(s):  
M. G. Pearson
Keyword(s):  
Real Time ◽  
Kalman Filtering ◽  
The Other ◽  
Estimation Methods ◽  
Weighted Mean ◽  
Modern Approach ◽  
On Line ◽  
Computer Based ◽  
And Control ◽  
The Impact

Estimation methods and filtering techniques are nowadays an integral part of any computer-based navigation system. The purpose of these techniques is to provide an estimate of required variables which is sufficiently accurate for real-time command and control purposes. Repeatability, which is important for so many applications, is deemed to be a by-product of the estimation process. For this requirement it is not strictly necessary for the process to be accurate, it is sufficient if it is only consistent; these are closely linked but one does not imply the other. The modern approach is to minimize the variance of the noisy observations or the sum of the squares of the residuals, and the methods available for doing this are increasingly refined. The impression given in the literature (and it is extensive) is that data processing can somehow compensate for the shortcomings of the basic sensors with respect to the operation being considered. Within certain limits this is true, but the real reason for the sudden surge of Kalman filtering for real-time on-line applications was the relative simplicity of the computational process. In a way, Kalman filtering has done for estimation theory what the Fast Fourier Transform has done for spectral analysis.The concept is simple enough to state. It consists of combining two independent estimates of a variable to form a weighted mean. One of these estimates is a forecast and the other is the current measurement.

Monitoring and control using on-line ORP on the continuous-flow activated sludge batch reactor system

1997 ◽  
Vol 35 (1) ◽  
pp. 57-66 ◽  
Author(s):  
R.-F. Yu ◽  
S.-L. Liaw ◽  
C.-N. Chang ◽  
H.-J. Lu ◽  
W.-Y. Cheng
Keyword(s):  
Process Control ◽  
Activated Sludge ◽  
Real Time ◽  
Continuous Flow ◽  
Batch Reactor ◽  
Fixed Time ◽  
Monitoring And Control ◽  
Time Control ◽  
On Line ◽  
And Control

On-line monitoring of ORP has been proved to be a practical and useful technique for process control of wastewater treatment systems. This paper presents the feasibility of using on-line ORP monitoring system on a laboratory scale single tank continuous-flow activated sludge batch reactor, which is capable of removing carbon, nitrogen and phosphorus pollutants. Two control strategies, fixed-time and real-time, are applied for process control. Results obtained from fixed-time control study indicate that the variations and the ORP profile can accurately represent dynamic characteristics of system; the pH profile can also indicate some of those characteristics. Also, the breakpoints, setpoints and settime on the ORP and pH profiles are used to establish the real-time control strategy to determine the transfer of operation stages. The real-time experiments show a better performance than fixed-time, thus, on-line ORP and pH monitoring and control is practical for continuous-flow batch activated sludge process control.

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