This paper describes a multipurpose and multidisciplinary control-systems laboratory that is being developed at the University of Colorado at Colorado Springs. It is shared by Electrical and Computer Engineering (ECE) and Mechanical and... more
This paper describes a multipurpose and multidisciplinary control-systems laboratory that is being developed at the University of Colorado at Colorado Springs. It is shared by Electrical and Computer Engineering (ECE) and Mechanical and Aerospace Engineering (MAE) students, allowing more efficient use of space and equipment, better use of funds, and elimination of overlap among individual departmental labs. The composition of
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This paper describes a multidisciplinary lab-based controls curriculum under development. One of the main focuses of the lab is that it be a multidisciplinary facility. It is shared by Electrical and Computer Engineering (ECE) and... more
This paper describes a multidisciplinary lab-based controls curriculum under development. One of the main focuses of the lab is that it be a multidisciplinary facility. It is shared by Electrical and Computer Engineering (ECE) and Mechanical and Aerospace Engineering (MAE) students. This arrangement allows more efficient use of space and equipment, better use of funds, and elimination of overlap among
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A critical element of a hybrid-electric-vehicle (HEV) propulsion system is the battery management system (BMS), which controls the performance of the HEV battery, the costliest and heaviest component of the propulsion system. This paper... more
A critical element of a hybrid-electric-vehicle (HEV) propulsion system is the battery management system (BMS), which controls the performance of the HEV battery, the costliest and heaviest component of the propulsion system. This paper examines the relevance and criticality of an HEV BMS as a whole; that is, its general functions and "responsibilities". Of these, its ability to accurately estimate
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Many problems in adaptive control can be divided into two parts; the first part is the control of plant dynamics, and the second is the control of plant disturbance. Very often, a single system is utilized to achieve both of these control... more
Many problems in adaptive control can be divided into two parts; the first part is the control of plant dynamics, and the second is the control of plant disturbance. Very often, a single system is utilized to achieve both of these control objectives. The approach of this paper treats each problem separately. Control of plant dynamics can be ac hieved
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At present, the control of a dynamic system (the '$plant") is generally done by means of feedback. This paper proposes an alternative approach that uses adaptive filtering to achieve feedforward control for both lin- ear and... more
At present, the control of a dynamic system (the '$plant") is generally done by means of feedback. This paper proposes an alternative approach that uses adaptive filtering to achieve feedforward control for both lin- ear and nonlinear plants. Precision is attained because of the feedback incorporated in the adaptive filtering. Disturbance in the plant can be optimally controlled by a
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The detection and disposal of anti-personnel land mines is one of the most difficult and intractable problems faced in ground confiict. This paper presents detection methods which use a separated-aperture microwave sensor and an... more
The detection and disposal of anti-personnel land mines is one of the most difficult and intractable problems faced in ground confiict. This paper presents detection methods which use a separated-aperture microwave sensor and an artificial neural-network pattern classifier. Several data-specific preprocessing methods are developed to enhance neuralnetwork learning. In addition, a generalized Karhunen-Loeve transform and the eigenspace separation transform are used to perform data reduction and reduce network complexity. Highly favorable results have been obtained using the above methods in conjunction with a feedforward neural network.
Adaptive control is seen as a two part problem: 1) control of plant dynamics, and 2) control of plant disturbance. The method proposed here, based on inverse control, treats the two problems separately without compromise. The method... more
Adaptive control is seen as a two part problem: 1) control of plant dynamics, and 2) control of plant disturbance. The method proposed here, based on inverse control, treats the two problems separately without compromise. The method applies to SISO and MIMO linear plants, and to nonlinear plants. An unknown linear plant will track an input command signal if the
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The battery management system (BMS) of a hybrid- electric-vehicle (HEV) battery pack comprises hardware and software to monitor pack status and optimize performance. One of its important functions is to execute algorithms that... more
The battery management system (BMS) of a hybrid- electric-vehicle (HEV) battery pack comprises hardware and software to monitor pack status and optimize performance. One of its important functions is to execute algorithms that continuously estimate battery state-of-charge (SOC), state-of-health (SOH), and available power. The primary difficulty when validating these algorithms is that there are no sensors that can measure SOC,
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At present, the control of a dynamic system (the “plant”) is generally done by means of feedback. This paper proposes an alternative approach that uses adaptive filtering to achieve feedforward control for both linear and nonlinear... more
At present, the control of a dynamic system (the “plant”) is generally done by means of feedback. This paper proposes an alternative approach that uses adaptive filtering to achieve feedforward control for both linear and nonlinear plants. Precision is attained because of the feedback incorporated in the adaptive filtering. Disturbance in the plant can be optimally controlled by a special
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A critical element of a hybrid-electric-vehicle (HEV) propulsion system is the battery management system (BMS), which controls the performance of the HEV battery, the costliest and heaviest component of the propulsion system. This paper... more
A critical element of a hybrid-electric-vehicle (HEV) propulsion system is the battery management system (BMS), which controls the performance of the HEV battery, the costliest and heaviest component of the propulsion system. This paper examines the relevance and criticality of an HEV BMS as a whole; that is, its general functions and "responsibilities". Of these, its ability to accurately estimate and report the state-of- charge (SOC) is arguably the most important. This paper will explain why SOC estimation is important, and will examine advances in the state of the art of SOC estimation methods, with a focus on Kalman Filter techniques.
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ABSTRACT Battery cell life depends critically on how the cell is used. Therefore, battery chargers and battery management systems must be designed to control cell usage carefully. In order to design optimal battery controls that effect a... more
ABSTRACT Battery cell life depends critically on how the cell is used. Therefore, battery chargers and battery management systems must be designed to control cell usage carefully. In order to design optimal battery controls that effect a tradeoff between cell performance (in some sense) and cell life, a model of cell degradation is necessary. This model must be simple and incremental in order to be implemented by an inexpensive microcontroller. This paper takes a first step toward developing such a controls-oriented comprehensive cell degradation model by deriving a reduced-order model of a single mechanism: the growth process of the solid-electrolyte interphase (SEI) layer, along with the resulting resistance rise and capacity loss. This reduced-order model approximates a physics-based PDE model from the literature, is simple and accurate, and may be used in optimal strategies for controlling lithium-ion batteries.
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ABSTRACT Battery cell life depends critically on how the cell is used. Therefore, battery chargers and battery management systems must be designed to control cell usage carefully. In order to design optimal battery controls that effect a... more
ABSTRACT Battery cell life depends critically on how the cell is used. Therefore, battery chargers and battery management systems must be designed to control cell usage carefully. In order to design optimal battery controls that effect a tradeoff between cell performance (in some sense) and cell life, a model of cell degradation is necessary. This model must be simple and incremental in order to be implemented by an inexpensive microcontroller. This paper takes a first step toward developing such a controls-oriented comprehensive cell degradation model by deriving a reduced-order model of a single mechanism: lithium deposition on overcharge, along with the resulting resistance rise and capacity loss. This reduced-order model approximates a physics-based PDE model from the literature, is simple and accurate, and may be used in optimal strategies for controlling lithium ion batteries.
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ABSTRACT This paper introduces the “discrete-time realization algorithm” (DRA) as a method to find a reduced-order, discrete-time realization of an infinite-order distributed-parameter system such as a transcendental impedance function.... more
ABSTRACT This paper introduces the “discrete-time realization algorithm” (DRA) as a method to find a reduced-order, discrete-time realization of an infinite-order distributed-parameter system such as a transcendental impedance function. In contrast to other methods, the DRA is a bounded-time deterministic method that produces globally optimal reduced-order models. In the DRA we use the sample and hold framework along with the inverse discrete Fourier transform to closely approximate the discrete-time impulse response. Next, the Ho–Kalman algorithm is used to produce a state-space realization from this discrete-time impulse response. Two examples are presented to demonstrate the DRA using low-order rational-polynomial transfer functions, where the DRA solution can be compared to known solutions. A third example demonstrates the DRA with a transcendental impedance function model of lithium diffusion in the solid phase of a lithium-ion battery, showing that a third-order discrete-time model can closely approximate this infinite-order model behavior.
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ABSTRACT We present a method to produce a physics-based one-dimensional discrete-time state-space reduced-order model (ROM) of a lithium-ion cell. The resulting ROM can predict the five variables of a standard porous-electrode... more
ABSTRACT We present a method to produce a physics-based one-dimensional discrete-time state-space reduced-order model (ROM) of a lithium-ion cell. The resulting ROM can predict the five variables of a standard porous-electrode model—reaction flux, solid and electrolyte lithium concentration, and solid and electrolyte potentials—at any location across the cell cross section, as well as cell terminal voltage. The method to generate the model involves first linearizing the porous-electrode-model equations, and then deriving closed-form Laplace-domain transfer functions from the linearized equations. Next, the discrete-time realization algorithm (DRA) is used to convert the transfer functions into an optimal discrete-time state-space realization. Advantages of this approach include that the DRA avoids nonlinear optimization and gives a straightforward method for selecting the system order for the ROM. Simulation results demonstrate that the ROM cell voltage predictions and the ROM internal electrochemical variable predictions match very closely with results obtained by simulating the full nonlinear porous-electrode partial differential equations.
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Research Interests: Neural Network, Multidisciplinary, Face Detection, Artificial Neural Networks, Data Reduction, and 10 moreFeature Extraction, Detectors, Application of Neural Network, Feedforward Neural Network, Pattern Classification, Apertures, Mine Detection, Artificial Neural Network, Karhunen Loeve Transform, and Land Mine Detection
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ABSTRACT Li-ion batteries swell due to gas evolution that results from decomposition of the electrolyte and from reaction with impurities. To study dimensional changes in Li battery cells, we derive a model for gas-evolution induced... more
ABSTRACT Li-ion batteries swell due to gas evolution that results from decomposition of the electrolyte and from reaction with impurities. To study dimensional changes in Li battery cells, we derive a model for gas-evolution induced volume fraction changes in both electrolyte and inert material phases in composite Li-ion electrodes. The nonlinear increase in cell resistance is explained using volume fraction changes within the context of physics-based modeling. The simulation results given here are also used to map the effects of volume fraction changes on the discharge curve and on heat generation.
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Typically, battery models are complex and difficult to parameterize to match real-world data. Achieving a good generalized fit between measured and simulated results should be done using a variety of laboratory data. Numerical... more
Typically, battery models are complex and difficult to parameterize to match real-world data. Achieving a good generalized fit between measured and simulated results should be done using a variety of laboratory data. Numerical optimizations can ensure the best possible fit between a simulation model and measured data, given a set of constraints. In this paper, we propose a semi-automated process