Equivalent Consumption Minimization Strategy With Consideration of Battery Aging for Parallel Hybrid Electric Vehicles

The equivalent consumption minimization strategy (ECMS) is a well-known energy management strategy for Hybrid Electric Vehicles (HEV). ECMS is very computationally efficient since it yields an instantaneous optimal control. ECMS has been shown to minimize fuel consumption under certain conditions. But, minimizing the fuel consumption often leads to excessive battery damage. This paper introduces a new optimal control problem where the cost function includes terms for both fuel consumption and battery aging. The Ah-throughput method is used to quantify battery aging. ECMS (with the appropriate equivalence factor) is shown to also minimize the cost function that incorporates battery aging. Simulation results show that the proposed aging ECMS algorithm significantly improves battery aging with little or no fuel economy penalty compared to ordinary ECMS

Are file review-based SAVRY ratings of violence risk reliable?

Since its publication a decade ago, the Structured Assessment for Violence Risk in Youth (SAVRY) has gained acceptance as a strong predictor of future violence in adolescent populations. Clinicians scoring the SAVRY use their professional judgment to code a structured protocol of risk and protective factors based on clinical interviews, a review of the juvenile’s records, and other sources of information. Much of the SAVRY validation research, however, has relied upon retrospective ratings obtained solely through file review. To date, no study has examined the reliability of file review-based SAVRY ratings. This study examined whether file-only SAVRY ratings are comparable to expert clinical ratings obtained through standard SAVRY administration procedures. Results indicate that file-only raters were unable to provide Summary Risk Ratings for 43% of the files and were unable to rate 53% of the SAVRY’s individual items. The ratings that were coded by the file-only raters had low to moderate levels of agreement with the expert ratings. These results suggest that file-only SAVRY coding is not a reliable manner in which to obtain risk assessment ratings, but the current findings conflict with low rates of missing data in previous file-only SAVRY research. Further research should therefore be undertaken to provide greater clarity as to whether file-only SAVRY ratings of violence risk are reliable.Ph.D., Clinical Psychology -- Drexel University, 201

Resume of Jeffrey Brian Burl, 1988-08

Naval Postgraduate School Faculty Resume[Burl joined] the Department of Electrical and Computer Engineering at the Naval Postgraduate School as an Assistant Professor in August of 1987

Wavelet-based burst system model change detection

A new scheme for detecting system burst changes is developed based on the continuous wavelet transform (CWT). The system is concisely represented by its time-frequency representation (TFR), the ratio of the CWTs of the output and the input. The TFR is first estimated, assuming that no system changes occur during a time period. A chi-square test is then executed to test the TFR estimate\u27s match to the data. System model changes are detected at the time samples when the assumption that the system is time invariant is broken. Simulations verify the capability of the proposed algorithm to detect burst system changes

Effects of time horizon on Model Predictive Control for Hybrid Electric Vehicles

© 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.. One of the challenges in Model Predictive Control (MPC) for Hybrid Electric Vehicles (HEVs), is real time implementation, Bo-Ah et al. (2012). Computation time can be reduced by limiting the time horizon of the prediction. Limiting the time horizon results in sub optimal control, but may yield nearly optimal control if the time horizon is chosen appropriately. This paper investigates the sensitivity of MPC to predicted horizon length with regard to Fuel Economy (FE). The results show that predicting Driver\u27s Desired Power (DDP) for the next 10 seconds on the highway and 20 seconds in the city, is sufficient for MPC to perform close to the Globally Optimized Controller (GOC). In other words: Regarding fuel economy optimization on the highway, knowing DDP for the next 10 seconds is almost equivalent to knowing the DDP for the whole trip

Continuous wavelet based linear time-varying system identification

A systematic framework is developed to address the parametric linear time-varying system identification problem, using the continuous wavelet transform (CWT). The system is modeled by a differential equation with unknown parameters and identified via the timefrequency representation, the ratio of the CWTs of the output and the input. The efficient execution of this system identification algorithm requires selecting appropriate scales from the wavelet transform. Scale selection can be formulated as an optimization problem: find a set of scales that contains the most information about the system\u27s dynamics and has high signal to noise ratio. In addition, selecting scales that have a minimum amount of redundant information is desirable. Three candidate selection metrics are presented that address these criteria and are based on an analytic investigation of the wavelet transform\u27s probabilistic structure. Finally, a non-linear least squares algorithm, coupled with a scale selection algorithm, is presented to identify the system model. Simulations and experiments verify this algorithm\u27s capability of tracking different types of model variation. © 2010 Elsevier B.V

Prediction of vehicle velocity for model predictive control

© 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.. In model predictive control, knowledge about the future trajectories of the set points or disturbances is used to optimize the overall system performance, Camacho and Bordons (2007). For hybrid electric vehicles, by predicting the future Driver\u27s Desired Velocity (DDV), fuel economy, or emissions can be improved, Debert et al. (2010). For predicting DDV, different approaches have been suggested, for example, artificial neural networks, Fotouhi et al. (2011), statistical methods, or methods based on GPS and Geographical Information Systems(GIS), Keulen et al. (2009). In this work, some of these approaches are introduced and autoregressive methods with GPS/GIS information are evaluated

Control strategies for a series-parallel hybrid electric vehicle

Living in the era of rising environmental sensibility and increasing gasoline prices, the development of a new environmentally friendly generation of vehicles becomes a necessity. Hybrid electric vehicles are one means of increasing propulsion system efficiency and decreasing pollutant emissions. In this paper, the series-parallel power-split configuration for Michigan Technological University\u27s FutureTruck is analyzed. Mathematical equations that describe the hybrid power-split transmission are derived. The vehicle\u27s differential equations of motion are developed and the system\u27s need for a controller is shown. The engine\u27s brake power and brake specific fuel consumption, as a function of its speed and throttle position, are experimentally determined. A control strategy is proposed to achieve fuel efficient engine operation. The developed control strategy has been implemented in a vehicle simulation and in the test vehicle. Simulation and experimental results are presented and discussed. The control strategy leads to a series hybrid vehicle behavior at low speeds and parallel hybrid vehicle behavior at highway speeds. Furthermore, the strategy ensures charge sustaining vehicle operation

Nonlinear correlation for estimating the motion of multiple objects in image sequences

A nonlinear correlation algorithm is proposed for estimating the motion of objects from an image pair. This algorithm requires no a priori information on the number, size, or shape of the moving objects and does not require feature extraction or segmentation of either image. The algorithm directly yields information on the number of moving objects, the motion of the objects, and the size of the objects. Additional processing can be performed to yield the centroid of the objects in either frame. The utility of the resulting algorithm is demonstrated by application to a pair of example image sequences. © 2001 Optical Society of America

Adaptive quaternion feedback regulation for eigenaxis rotations

The article of record as published may be found at http://dx.doi.org/10.2514/321346A controller to rotate a rigid body between two successive orientations is designed. Particular features are the fact that it is based on the quaternion approach, known to provide singularity-free attitude description, and it is adaptive in the sense that it does not need specific knowledge of the inertia matrix. Global stability of the overall controller is proved analytically and tested in computer simulations