Geoffrey A. Williamson

Constant power loads and negative impedance instability in automotive systems: definition, modeling, stability, and control of power electronic converters and motor drives

Power electronic converters and electric motor drives are being put into use at an increasingly rapid rate in advanced automobiles. However, the new advanced automotive electrical systems employ multivoltage level hybrid ac and dc as well as electromechanical systems that have unique characteristics, dynamics, and stability problems that are not well understood due to the nonlinearity and time dependency of converters and because of their constant power characteristics. The purpose of this paper is to present an assessment of the negative impedance instability concept of the constant power loads (CPLs) in automotive power systems. The main focus of this paper is to analyze and propose design criteria of controllers for automotive converters/systems operating with CPLs. The proposed method is to devise a new comprehensive approach to the applications of power electronic converters and motor drives in advanced automotive systems. Sliding-mode and feedback linearization techniques along with large-signal phase plane analysis are presented as methods to analyze, control, and stabilize automotive converters/systems with CPLs

Protective Importance of the Myogenic Response in the Renal Circulation

Primary essential hypertension is second only to diabetic nephropathy as a etiology for end-stage renal disease.1 In addition, coexistent/superimposed hypertension plays a major role in the progression of most forms of chronic kidney disease (CKD), including diabetic nephropathy.2–5 Nevertheless, the individual risk is very low, with <1% of the hypertensive population developing end-stage renal disease. Such data indicate that there must be mechanisms that normally protect the kidneys from hypertensive injury of a severity sufficient to result in end-stage renal disease. The following Brief Review summarizes the evidence that indicates that the renal autoregulatory response, primarily mediated by the myogenic mechanism, is largely responsible for such protection. Moreover, the differing patterns of renal damage that are observed in clinical and experimental hypertension are best explained when considered in the context of alterations in the renal autoregulatory capacity. Recent data also indicate that hypertensive renal damage correlates most strongly with systolic blood pressure (BP).6–8 Accordingly, the review further emphasizes the kinetic characteristics of the renal myogenic response to oscillating BP signals that render it particularly capable of providing protection against systolic pressures. Most individuals with primary hypertension develop the modest vascular pathology of benign nephrosclerosis.5 The glomeruli are largely spared, and, therefore, proteinuria is not a prominent feature. Because it progresses fairly slowly with limited ischemic nephron loss, renal function is not seriously compromised, except in some genetically susceptible individuals or groups, such as blacks, in whom a more accelerated course may be seen.2–5 Thus, the slope of the relationship between renal damage and BP through most of the hypertensive range is fairly flat in individuals with benign nephrosclerosis.2–4 However, if the hypertension becomes very severe and exceeds a critical threshold, severe acute disruptive injury of malignant nephrosclerosis to the renal arteries and arterioles develops …

Loop-Cancellation Technique: A Novel Nonlinear Feedback to Overcome the Destabilizing Effect of Constant-Power Loads

Tightly regulated closed-loop converters are problematic when used as a load since they tend to draw constant power and exhibit negative incremental resistance. This negative resistance causes stability problems for the feeder system, whether it is an input filter or another converter. In multiconverter power electronic systems, which exist in different land, sea, air, and space vehicles, including electric, hybrid, plug-in hybrid, and fuel-cell vehicles, there are many converters loaded by other converters. Therefore, the destabilizing effect of the load converters, which are called constant-power loads, is a major issue. In this paper, a novel nonlinear feedback, which is called loop cancellation, is introduced. This technique is used to cancel the destabilizing effect of the constant-power loads. Theoretically, any amount of constant-power load can be compensated by this technique, and it can identically be implemented on different types of converters. The effectiveness of the proposed technique has been verified by PSpice simulations and experimental results.

Reduced complexity Volterra models for nonlinear system identification

A broad class of nonlinear systems and filters can be modeled by the Volterra series representation. However, its practical use in nonlinear system identification is sometimes limited due to the large number of parameters associated with the Volterra filter’s structure. The parametric complexity also complicates design procedures based upon such a model. This limitation for system identification is addressed in this paper using a fixed pole expansion technique (FPET) within the Volterra model structure. The FPET approach employs orthonormal basis functions derived from fixed (real or complex) pole locations to expand the Volterra kernels and reduce the number of estimated parameters. That the performance of FPET can considerably reduce the number of estimated parameters is demonstrated by a digital satellite channel example in which we use the proposed method to identify the channel dynamics. Furthermore, a gradient-descent procedure that adaptively selects the pole locations in the FPET structure is developed.

Globally convergent adaptive IIR filters based on fixed pole locations

A new class of adaptive filters, dubbed fixed pole adaptive filters (FPAFs), is introduced. These adaptive filters have infinite impulse responses, yet their adaptation exhibits provable global convergence. Good filter performance with a relatively small number of adapted parameters is permitted by the new filter structure, thus reducing the computational burden needed to implement adaptive filters. The implementation and computational complexity of the FPAF is described, and its modeling capabilities are determined. Excitation conditions on the filter input are established that guarantee global convergence of a standard set of adaptive algorithms. Some methods are described for selecting the fixed pole locations based on a priori information regarding the operating environment of the adaptive filter. The FPAF is tailored to applications by such a procedure, enabling improved performance. In examples, the FPAF is shown to achieve a smaller minimum mean square error, given an equal number of adapted parameters, in comparison with adaptive FIR filters and adaptive filters based on Laguerre and Kautz models.

Constant power loads and negative impedance instability in sea and undersea vehicles: statement of the problem and comprehensive large-signal solution

Power electronic converters are usually loaded by passive loads or combinations of passive elements and voltage and current sources. However, there is an emerging vehicular system configuration where converters are loaded by power converters and a better model for the load is a constant power model. This converter operation appears in multi-converter applications such as advanced sea and undersea vehicles where a main converter has as loads a set of converters operating in closed-loop with tight output voltage regulation. This set of converters present at the input terminals a dynamic behavior similar to a constant power load (CPL) for a range of input voltages and a frequency span that ranges from DC up to the bandwidth of the converters. The primary goal of this paper is the development and extension of a technique for large-signal analysis of power electronic converters operating with constant power loads in sea and undersea vehicles using a phase plane analysis. This proposed approach could be used to present advantages and limitations of different controllers and, based on that analysis, define the selection and synthesis of controllers to achieve the required performance and robustness of the system.

Performance characteristics of the median LMS adaptive filter

The median least-mean-square (MLMS) adaptive filter alleviates the problem of degradation of performance when inputs are corrupted by impulsive noise by protecting the filter coefficients from the impact of the impulses. MLMS is obtained from the least mean square (LMS) by applying a median operation to the raw gradient estimates of the mean-squared-error performance surface. The algorithm is analyzed for the class of independent and identically distributed inputs, establishing exponential convergence. The rate of convergence is shown to depend on order statistics of the input but shows little dependence on characteristics of the impulsive interference. Analysis of the steady-state performance indicates a significantly improved performance for MLMS compared to LMS. Analytic predictions for both convergence and steady-state behavior are supported by simulations. >

Large-signal analysis of a DC-DC buck power converter operating with constant power load

The dynamic properties of the buck converter operating with a constant power load are studied in this paper. This configuration is present in DC-DC converters feeding power converters tightly regulated in multi-converter power electronics systems. The dynamic behavior of converters loaded by constant power loads differs from the behavior of converters loaded by resistors or current generators. The purpose of this paper is to address the closed-loop behavior of the buck converter feeding a constant power load. Based on a comprehensive large-signal analysis of the converter, the basin of attraction of the equilibrium point is defined. This region, in general, excludes the low range of the output voltage affecting the transient stability, forcing proper coordination between the converter and loads during start-up.

Large BP-dependent and -independent differences in susceptibility to nephropathy after nitric oxide inhibition in Sprague-Dawley rats from two major suppliers

The N(ω)-nitro-l-arginine methyl ester (l-NAME) model is widely employed to investigate the role of nitric oxide (NO) in renal injury. The present studies show that Sprague-Dawley rats from Harlan (H) and Charles River (CR) exhibit strikingly large differences in susceptibility to l-NAME nephropathy. After 4 wk of l-NAME (∼50 mg·kg(-1)·day(-1) in drinking water), H rats (n = 13) exhibited the expected hypertension [average radiotelemetric systolic blood pressure (BP), 180 ± 3 mmHg], proteinuria (136 ± 17 mg/24 h), and glomerular injury (GI) (12 ± 2%). By contrast, CR rats developed less hypertension (142 ± 4), but surprisingly no proteinuria or GI, indicating a lack of glomerular hypertension. Additional studies showed that conscious H, but not CR, rats exhibit dose-dependent renal vasoconstriction after l-NAME. To further investigate these susceptibility differences, l-NAME was given 2 wk after 3/4 normotensive nephrectomy (NX) and comparably impaired renal autoregulation in CR-NX and H-NX rats. CR-NX rats, nevertheless, still failed to develop proteinuria and GI despite moderate hypertension (144 ± 2 mmHg, n = 29). By contrast, despite an 80-90% l-NAME dose reduction and lesser BP increases (169 ± 4 mmHg), H-NX rats (n = 20) developed greater GI (26 ± 3%) compared with intact H rats. Linear regression analysis showed significant (P < 0.01) differences in the slope of the relationship between BP and GI between H-NX (slope 0.56 ± 0.14; r = 0.69; P < 0.008) and CR-NX (slope 0.09 ± 0.06; r = 0.29; P = 0.12) rats. These data indicate that blunted BP responses to l-NAME in the CR rats are associated with BP-independent resistance to nephropathy, possibly mediated by a resistance to the renal (efferent arteriolar) vasoconstrictive effects of NO inhibition.

QR-based TLS and mixed LS-TLS algorithms with applications to adaptive IIR filtering

The least squares (LS), total least squares (TLS), and mixed LS-TLS approaches are compared as to their properties and performance on several classical filtering problems. Mixed LS-TLS is introduced as a QR-decomposition-based algorithm for unbiased, equation error adaptive infinite impulse response (IIR) filtering. The algorithm is based on casting adaptive IIR filtering into a mixed LS-TLS framework. This formulation is shown to be equivalent to the minimization of the mean-square equation error subject to a unit norm constraint on the denominator parameter vector. An efficient implementation of the mixed LS-TLS solution is achieved through the use of back substitution and inverse iteration. Unbiasedness of the system parameter estimates is established for the mixed LS-TLS solution in the case of uncorrelated output noise, and the algorithm is shown to converge to this solution. LS, TLS, and mixed LS-TLS performance is then compared for the problems of echo cancellation, noise reduction, and frequency equalization.