Detection of Vehicle Tripped and Untripped Rollovers by a Novel Index With Mass-Center-Position Estimations

This paper presents a novel mass-center-position (MCP) metric for vehicle rollover propensity detection. MCP is first determined by estimating the positions of the center of mass of one sprung mass and two unsprung masses with two switchable roll motion models, before and after tire lift-off. The roll motion information without saturation can then be provided through MCP continuously. Moreover, to detect completed rollover statues for both tripped and untripped rollovers, the criteria are derived from d’Alembert principle and moment balance conditions based on MCP. In addition to tire lift-off, three new rollover statues, rollover threshold, rollover occurrence, and vehicle jumping into air can be all identified by the proposed criteria. Compared with an existing rollover index, lateral load transfer ratio, the fishhook maneuver simulation results in CarSim® for an E-class SUV show that MCP metric can successfully predict the vehicle impending rollover without saturation for untripped rollovers. Tripped rollovers caused by a triangle road bump are also successfully detected in the simulation. Thus, MCP metric can be successfully applied for rollover propensity prediction.

Real-Time Optimization of Wind Farm Energy Capture With Delay Compensated Nested-Loop Extremum Seeking Control

Real-time optimization of wind farm energy capture for below rated wind speed is critical for reducing the levelized cost of energy (LCOE). Performance of model based control and optimization techniques can be significantly limited by the difficulty in obtaining accurate turbine and farm models in field operation, as well as the prohibitive cost for accurate wind measurements. The Nested-Loop Extremum Seeking Control (NLESC), recently proposed as a model free method has demonstrated its great potential in wind farm energy capture optimization. However, a major limitation of previous work is the slow convergence, for which a primary cause is the low dither frequencies used by upwind turbines, primarily due to wake propagation delay through the turbine array. In this study, NLESC is enhanced with the predictor based delay compensation proposed by Oliveira and Krstic [1], which allows the use of higher dither frequencies for upwind turbines. The convergence speed can thus be improved, increasing the energy capture consequently. Simulation study is performed for a cascaded three-turbine array using the SimWindFarm platform. Simulation results show the improved energy capture of the wind turbine array under smooth and turbulent wind conditions, even up to 10% turbulence intensity. The impact of the proposed optimization methods on the fatigue loads of wind turbine structures is also evaluated.

Modified Zero Time Delay Input Shaping for Industrial Robot With Flexibility

Although input shaping is an effective approach for vibration suppression in a variety of applications, the time delay introduced is not desired. Current techniques to reduce the time delay can not guarantee zero delay or may cause non-smooth motion, which is harmful for the actuators. In order to address such issue, a modified zero time delay input shaping is proposed in this paper. Experimental results show the advantage of the proposed approach.

Physics-Based Friction Model With Potential Application in Numerical Models for Tire-Road Traction

Good understanding of friction in tire-road interaction is of critical importance for vehicle dynamic control systems. Most of the friction models proposed to describe the friction coefficient between tire-treads and road surfaces have been developed based on empirical or semi-empirical relations that are not able to include many effective parameters involved in the tire-road interactions. Therefore, these models are just useful in limited conditions similar to the experiments, and do not accurately represent tire-road traction in numerical tire models. However, in last two decades, a few theoretical models have been developed to calculate the tire-road friction coefficient theoretically by considering both viscoelastic behavior of tire tread compounds and multi-scale interactions between tire treads and rough road surfaces. In this article, a novel physics-based model proposed by Persson has been investigated and used to develop computer algorithms for calculation of sliding friction coefficient between a tire tread compound and a rough substrate. The viscoelastic behavior of tread compound and the surface profile of rough counter surface are the inputs of this physics-based theoretical model. The numerical results of the model have been compared with the experimental results obtained from a dynamic friction tester designed and built in the Center for Tire Research (CenTire). Good agreement between numerical results of theoretical model and experimental results has been found at intermediate range of slip velocities considering the effect of adhesion and shearing in the real contact area in addition to hysteresis friction due to internal energy dissipation in the tire tread compound.

High Frequency Analysis of a Dynamically Coupled Parallel Plate System

The behavior of a system comprised of two parallel plates coupled by a discrete, linear spring and damper is studied. Classical Modal Analysis (CMA) is used to illustrate this behavior, while specifically observing the effects of varying the stiffness and damping ratio of the coupling elements. Conditions under which the coupling may be approximated as rigid are identified. Additionally, conditions under which the coupling displacement reaches its maximum and minimum values are identified. This work also lays the groundwork for extending Asymptotic Modal Analysis (AMA) to systems with discrete, elastic, and dissipative coupling.

Customer Usage Based on Pseudo Damage

Modeling customer usage in vehicle applications is critical in performing durability simulations and analysis in early design stages. Currently, customer usage is typically based on road roughness (some measure of accumulated suspension travel), but vehicle damage does not vary linearly with the road roughness. Presently, a method for calculating a pseudo damage measure is developed based on the roughness of the road profile, specifically the International Roughness Index (IRI). The IRI and pseudo damage are combined to create a new measure referred to as the road roughness-insensitive pseudo damage. The road roughness-insensitive pseudo damage measure is tested using a weighted distribution of IRI values corresponding to the principal arterial (highways and freeways) road type from the Federal Highway Administration (FHWA) Highway Performance Monitoring System (HPMS) dataset. The weighted IRI distribution is determined using the number of unique IRI occurrences in the functional road type dataset and the Average Annual Daily Traffic (AADT) provided in the FHWA HPMS data.

SCR Control System Design Based on On-Line Radial Basis Function and Backpropagation Neural Networks

Because of its high NOx reduction efficiency, selective catalyst reduction (SCR) has become an indispensable part of diesel vehicle aftertreatment. This paper presents a control strategy for SCR systems that is based on an on-line radial basis function neural network (RBFNN) and an on-line backpropagation neural network (BPNN). In this control structure, the radial basis function neural network is employed as an estimator to provide Jacobian information for the controller; and the backpropagation neural network is utilized as a controller, which dictates the appropriate urea-solution to be injected into the SCR system. This design is tested by simulations based in Gamma Technologies software (GT-ISE) as well as MATLAB Simulink. The results show that the RBF-BPNN control technique achieves a 1–5 % higher NOx reduction efficiency than a PID controller.

ARX Model of a Residential Heating System With Backpropagation Parameter Estimation Algorithm

Model predictive control (MPC) strategies hold great potential for improving the performance and energy efficiency of building heating, ventilation, and air-conditioning (HVAC) systems. A challenge in the deployment of such predictive thermo-static control systems is the need to learn accurate models for the thermal characteristics of individual buildings. This necessitates the development of online and data-driven methods for system identification. In this paper, we propose an autoregressive with exogenous terms (ARX) model of a thermal zone within a building. To learn the model, we present a backpropagation approach for recursively estimating the parameters. Finally, we fit the linear model to data collected from a residential building with a forced-air heating and ventilation system and validate the accuracy of the trained model.

A Communication-Free Decentralized Power Control Approach for Power Loss Minimization in Islanded Microgrids Using Extremum Seeking

This paper considers islanded microgrids and is motivated by the need for decentralized control strategies with minimal communication among grid components to support a robust and plug-and-play operation. We focus on the problem of power allocation among the distributed generation units (DGs) to maintain low distribution power loss in the grid and develop a communication-free distributed power control approach for power loss minimization based on the extremum-seeking (ES) method. In this approach, the DGs implement ES simultaneously and separately to minimize their current outputs by controlling the active power. The total power loss is thus reduced and no grid structure information or communication is needed in the optimization process. The existence of a Nash equilibrium in the resulting non-cooperative game is proved. Numerical simulations are conducted to demonstrate the performance of the proposed communication-free power control approach and show that it is suitable for maintaining low power loss under different operating conditions in a plug-and-play manner.

Study of an Impact Driven Frequency Up-Conversion Piezoelectric Harvester

Frequency up-conversion is an effective way to increase the output power from a piezoelectric beam, which converts the ambient low-frequency vibration to the resonant vibration of the piezoelectric energy harvesters (PEH) to achieve high electric power output. Frequency up-conversion technologies are realized via impact or non-impact magnetic force to mediate the interaction between the driving beam and the generating beam. Most studies focus on the either linear model prediction or experimental verification of the linear analysis. Few, if any, study the effects of the impact induced nonlinear phenomena on power generation efficiency. In this work, we investigate how to use discontinuous theory to improve the power efficiency of the frequency up-conversion process caused by impacts. The energy harvesting performance of a piezoelectric beam in interaction with a softer beam in periodic motion is studied. The discontinuous dynamical system theory is applied to this problem to study the piezoelectric behavior under periodic motions and its bifurcations. The beams are modeled with two spring-mass-damper systems, and the analytical model of the piezoelectric beam is created based on the linear mechanical-electrical constitutive law of the piezoelectric material, and the linear elastic constitutive law of the substrate. Based on the theoretical model, the analytical solution of the output power is derived in terms of the vibration amplitude, frequency, and the electrical load. The soft beam is subjected to a sinusoidal base excitation, and the impacts of the more flexible beam excite the piezoelectric beam. The performance of the energy harvesting of period one and period two motions have been studied and bifurcation trees for impact velocities, times, displacements and harvested power versus the frequency of the base excitation are obtained.