Variable Parameter Self-Adaptive Control Strategy Based on Driving Condition Identification for Plug-In Hybrid Electric Bus

A variable parameter self-adaptive control strategy based on driving condition identification is proposed to take full advantage of the fuel saving potential of the plug-in hybrid electric bus(PHEB).Firstly,the principal component analysis(PCA)and the fuzzy c-means clustering(FCM)algorithm is used to construct the comprehensive driving cycle,congestion driving cycle,urban driving cycle and suburban driving cycle of Chinese urban buses.Secondly,an improved particle swarm optimization(IPSO)algorithm is proposed,and is used to optimize the control parameters of PHEB under different driving cycles,respectively.Then,the variable parameter self-adaptive control strategy based on driving condition identification is given.Finally,for an actual running vehicle,the driving condition is identified by relevance vector machine(RVM),and the corresponding control parameters are selected to control the vehicle.The simulation results show that the fuel consumption of using the variable parameter self-adaptive control strategy is reduced by 4.2% compared with that of the fixed parameter control strategy,and the feasibility of the variable parameter self-adaptive control strategy is verified.

Influence of Spray Gun Position and Orientation on Liquid Film Development along a Cylindrical Surface

A method combining computationalfluid dynamics(CFD)and an analytical approach is proposed to develop a prediction model for the variable thickness of the spray-induced liquidfilm along the surface of a cylindrical workpiece.The numerical method relies on an Eulerian-Eulerian technique.Different cylinder diameters and positions and inclinations of the spray gun are considered and useful correlations for the thickness of the liquidfilm and its distribution are determined using various datafitting algorithms.Finally,the reliability of the pro-posed method is verified by means of experimental tests where the robot posture is changed.The provided cor-relation are intended to support the optimization of spray-based coating applications.

Evaluation of a Pulse Width Modulated Bypass Nozzle for the Development of a Variable Load Residential Oil Burner

Due to the need for energy conservation in buildings and the simultaneous benefit of cost savings, the development of a low firing rate load modulating residential oil burner is very desirable. One of the two main requirements of such a burner is the development of a burner nozzle that is able to maintain the particle size distribution of the fuel spray in the desirable (small) size range for efficient and stable combustion. The other being the ability to vary the air flow rate and air distribution around the fuel nozzle in the burner for optimal combustion at the current fuel firing rate. In this paper, which deals with the first requirement, we show that by using pulse width modulation in the bypass channel of a commercial off-the-shelf bypass nozzle, this objective can be met. Here we present results of spray patterns and particle size distribution for a range of fuel firing rates. The results show that a desirable fuel spray pattern can be maintained over a fuel firing rate turndown ratio (Maximum Fuel Flow Rate/Minimum Fuel Flow Rate) of 3.7. Thus here we successfully demonstrate the ability to electronically vary the fuel firing rate by more than a factor of 3 while simultaneously maintaining good atomization.

The control of welding wire feed self-adaptive mechanism based on fuzzy PID

The welding wire feed mechanism is an important component of welding equipment, both reliability and stabilization are the premise that the welding quality can be ensured. The PID is currently adapted to control the welding wire feed mechanism, although the fuzzy PID has advantage of fast response and adaptation, the precision of fuzzy PID is lower. Accordingly, the fuzzy self-adaptive PID controller was proposed through changing fuzzy input variables and output variables based on variable universe, simple furwtion is adopted as scaling factor, the fuzzy PID controller parameters are adjusted to improve the precision and adjustment range. Simulation results show that control effects of fuzzy self-adaptive PID adopted by the welding wire feed mechanism have good adaptive ability and robustness based on variable universe, the welding experiments indicate that the welding quality met the requirements actually.

Feature Model Configuration Reuse Scheme for Self-Adaptive Systems

Most large-scale systems including self-adaptive systems utilize feature models(FMs)to represent their complex architectures and benefit from the reuse of commonalities and variability information.Self-adaptive systems(SASs)are capable of reconfiguring themselves during the run time to satisfy the scenarios of the requisite contexts.However,reconfiguration of SASs corresponding to each adaptation of the system requires significant computational time and resources.The process of configuration reuse can be a better alternative to some contexts to reduce computational time,effort and error-prone.Nevertheless,systems’complexity can be reduced while the development process of systems by reusing elements or components.FMs are considered one of the new ways of reuse process that are able to introduce new opportunities for the reuse process beyond the conventional system components.While current FM-based modelling techniques represent,manage,and reuse elementary features to model SASs concepts,modeling and reusing configurations have not yet been considered.In this context,this study presents an extension to FMs by introducing and managing configuration features and their reuse process.Evaluation results demonstrate that reusing configuration features reduces the effort and time required by a reconfiguration process during the run time to meet the required scenario according to the current context.

MINIMUM ATTRIBUTE CO-REDUCTION ALGORITHM BASED ON MULTILEVEL EVOLUTIONARY TREE WITH SELF-ADAPTIVE SUBPOPULATIONS

Attribute reduction is an important process in rough set theory.Finding minimum attribute reduction has been proven to help the user-oriented make better knowledge discovery in some cases.In this paper,an efficient minimum attribute reduction algorithm is proposed based on the multilevel evolutionary tree with self-adaptive subpopulations.A model of multilevel evolutionary tree with self-adaptive subpopulations is constructed,and interacting attribute sets are better decomposed into subsets by the self-adaptive mechanism of elitist populations.Moreover it can self-adapt the subpopulation sizes according to the historical performance record so that interacting attribute decision variables are captured into the same grouped subpopulation,which will be extended to better performance in both quality of solution and competitive computation complexity for minimum attribute reduction.The conducted experiments show the proposed algorithm is better on both efficiency and accuracy of minimum attribute reduction than some representative algorithms.Finally the proposed algorithm is applied to magnetic resonance image(MRI)segmentation,and its stronger applicability is further demonstrated by the effective and robust segmentation results.

Droplet size and spray pattern characteristics of PWM-based continuously variable spray

A Pulse-Width-Modulation-based(PWM-based)continuously variable sprayer was developed using a proportional regulating solenoid valve.Variable flow-rate was obtained by varying the duty cycle of the actuating signal with 24 kHz frequency.Flow-rate regulating ranges of the PWM-based continuously variable spray(i.e.the turndown ratio responding to 100%-40%duty cycle)are 7.14:1,3.57:1,and 3.70:1 for flat-fan,hollow-cone and solid-cone nozzles,respectively.The purpose of the study was to evaluate the PWM-based continuously variable spray.The method was to quantify the effects of flow-rate control on spray characteristics in terms of droplet size spectra,spray distribution patterns,and spray angle for flat-fan,hollow-cone,solid-cone nozzles.For all nozzles tested,spray distribution concentrated on the center of the spray field with the decrease of flow-rate.But the spray shape is still symmetrical.The sensitivities of the spray angles to flow-rate were 0.83,0.67,and 0.58(o)/%respectively for flat-fan,hollow-cone and solid-cone nozzles.Compared with the sensitivities of spray angle for PWM-based intermittent variable spray,they are somewhat larger.As flow-rate was reduced from the maximum(100%flow-rate)to the minimum controllable rate,the observed median diameter of spray droplets decreased by 5.4%,9.8%,and 9.9%for flat-fan,hollow-cone and solid-cone nozzles,respectively.This indicates that spray droplet size was affected slightly by flow-rate control.

Vision-based adaptive variable rate spraying approach for unmanned aerial vehicles

The rapid developments of unmanned aerial vehicles(UAV)and vision sensor are contributing a great reformation in precision agriculture.Farmers can fly their UAV spraying pesticides around their crop fields while staying at their remote control room or any place that is separated from their farm land.However,there is a common phenomenon in rice planting management stage that some empty areas are randomly located in farmland.Therefore,a critical problem is that the waste of pesticides that occurs when spraying pesticides over rice fields with empty areas by using the common UAV,because it is difficult to control the flow accuracy based on the empty areas changing.To tackle this problem,a novel vision-based spraying system was proposed that can identify empty areas automatically while spraying a precise amount of pesticides on the target regions.By this approach,the image was preprocessed with the Lucy-Richardson algorithm,then the target area was split from the background with k-means and the feature parameters were extracted,finally the feature parameters were filtered out with a positive contribution which would serve as the input parameters of the support vector machine(SVM)to identify the target area.Also a fuzzy control model was analyzed and exerted to compensate the nonlinearity and hysteresis of the variable rate spraying system.Experimental results proved that the approach was applicable to reducing the amount of pesticides during UAV spraying,which can provide a reference for precision agriculture aviation in the future.