Research on Friction Compensation Control for Electric Power Steering System

A novel friction compensation control method is proposed to compensate both the dynamic and static friction torque of steering system. The change of EPS assist torque under fixed amplitude friction compensation torque can cause the diver’s steering feeling fuzzy. That is due to the fact that the friction torque felt by driver varies with EPS assist gain. Therefore, a further modified friction compensation control method is proposed based on EPS assist gain to make the driver have similar friction feeling. Finally, computer simulation and vehicle test are performed to verify the effectiveness of adaptation method in the proposed controller. Test results indicate that the proposed controller improved the driver’s steering performance

Slip Control of Electric Vehicle Based on Tire-Road Friction Coefficient Estimation

The real-time change of tire-road friction coefficient is one of the important factors that influence vehicle safety performance. Besides, the vehicle wheels’ locking up has become an important issue. In order to solve these problems, this paper comes up with a novel slip control of electric vehicle (EV) based on tire-road friction coefficient estimation. First and foremost, a novel method is proposed to estimate the tire-road friction coefficient, and then the reference slip ratio is determined based on the estimation results. Finally, with the reference slip ratio, a slip control based on model predictive control (MPC) is designed to prevent the vehicle wheels from locking up. In this regard, the proposed controller guarantees the optimal braking torque on each wheel by individually controlling the slip ratio of each tire within the stable zone. Theoretical analyses and simulation show that the proposed controller is effective for better braking performance

Multi-modal Fusion for Flasher Detection in a Mobile Video Chat Application

ABSTRACT This paper investigates the development of accurate and efficient classifiers to identify misbehaving users (i.e., "flashers") in a mobile video chat application. Our analysis is based on video session data collected from a mobile client that we built that connects to a popular random video chat service. We show that prior imagebased classifiers designed for identifying normal and misbehaving users in online video chat systems perform poorly on mobile video chat data. We present an enhanced image-based classifier that improves classification performance on mobile data. More importantly, we demonstrate that incorporating multi-modal mobile sensor data from accelerometer and the camera state (front/back) along with audio can significantly improve the overall image-based classification accuracy. Our work also shows that leveraging multiple image-based predictions within a session (i.e., temporal modality) has the potential to further improve the classification performance. Finally, we show that the cost of classification in terms of running time can be significantly reduced by employing a multilevel cascaded classifier in which high-complexity features and further image-based predictions are not generated unless needed

Assessing the Impact of EEE Standard on Energy Consumed by Commercial Grade Network Switches

This book chapter is adapted from [1] and it is closely linked to work published in [2] and [3]. Reducing power consumption of network equipment has been both driven by a need to reduce the ecological footprint of the cloud as well as the im-mense power costs of data centers. As data centers, core networks and conse-quently, the cloud, constantly increase in size, their power consumption should be mitigated. Ethernet, the most widely used access network still remains the biggest communication technology used in core networks and cloud infrastructures. The Energy-Efficient Ethernet or EEE standard introduced by IEEE in 2010, aims to reduce the power consumption of EEE ports by transitioning Ethernet ports into a low power mode when traffic is not present. As statistics show that the average utilization rate of ethernet links is 5 percent on desktops and 30 percent in data centers, the power saving potential of EEE could be immense. This research aims to assess the benefits of deploying EEE and create a power consumption model for network switches with and without EEE. Our measurements show that an EEE port runs at 12-15% of its total power when in low power mode. Therefore, the power savings can exceed 80% when there is no traffic. However, our measure-ments equally show that the power consumption of a single port represents less than 1% of the total power consumption of the switch. The base power consumed by the switch without any port is still significantly high and is not affected by EEE. Experiment results also show that the base power consumption of switches does not significantly increase with the size of the switches. Doubling the size of the switch between 24 and 48 ports increases power consumption by 35.39%. EEE has a greater effect on bigger switches, with a power (or energy) gain on the EEE-enabled 48-port switch compared to 2 x EEE-enabled 24-port switch. On the other hand, it seems to be more energy efficient to use 2 separate 24-port switches (NO EEE) than 2 separate 24-port switches (With EEE)

Integrated metabolomic and metagenomic strategies shed light on interactions among planting environments, rhizosphere microbiota, and metabolites of tobacco in Yunnan, China

Changes in climatic factors and rhizosphere microbiota led plants to adjust their metabolic strategies for survival under adverse environmental conditions. Changes in plant metabolites can mediate crop growth and development and interact with rhizosphere microbiota of the plant rhizosphere. To understand the interactions among environmental factors, rhizosphere microbiota, and metabolites of tobacco, a study was conducted by using integrated metagenomic and metabolomic strategies at four typical representative tobacco planting sites in Yunnan, China. The results showed that the agronomical and biochemical traits were significantly affected by temperature, precipitation (PREP), soil pH, and altitude. Correlation analyses revealed a significant positive correlation of temperature with length, width, and area of the leaf, while PREP correlated with plant height and effective leaf numbers. Furthermore, total sugar and reducing sugar contents of baked leaves were significantly higher, while the total nitrogen and total alkaloid levels were lower in tobacco leaves at site with low PREP. A total of 770 metabolites were detected with the highest number of different abundant metabolites (DMs) at Chuxiong (CX) with low PREP as compared to the other three sites, in which secondary metabolites were more abundant in both leaves and roots of tobacco. A total of 8,479 species, belonging to 2,094 genera with 420 individual bins (including 13 higher-quality bins) harboring 851,209 CDSs were detected. The phyla levels of microorganisms such as Euryarchaeota, Myxococcota, and Deinococcota were significantly enriched at the CX site, while Pseudomonadota was enriched at the high-temperature site with good PREP. The correlation analyses showed that the metabolic compounds in low-PREP site samples were positively correlated with Diaminobutyricimonas, Nissabacter, Alloactinosynnema, and Catellatospora and negatively correlated with Amniculibacterium, Nordella, Noviherbaspirillum, and Limnobacter, suggesting that the recruitment of Diaminobutyricimonas, Nissabacter, Alloactinosynnema, and Catellatospora in the rhizosphere induces the production and accumulation of secondary metabolites (SMs) (e.g., nitrogen compounds, terpenoids, and phenolics) for increasing drought tolerance with an unknown mechanism. The results of this study may promote the production and application of microbial fertilizers and agents such as Diaminobutyricimonas and Alloactinosynnema to assemble synthetic microbiota community or using their gene resources for better cultivation of tobacco as well as other crops in drought environments

A Middleware for Power Management in Multicore Smartphones

Increased power consumption is a critical concern for smartphone users. While multi-core processors in smartphones have already emerged in market, current applications are yet to take full advantage of this new architecture, particularly in the area of managing power consumption. This paper addresses the issue of managing power consumption in multicore smartphones via a middleware layer that schedules optimal number of cores for currently running applications taking into account the tradeoff between power consumption, performance and user experience. The paper first describes a simple and accurate method to measure the overall power consumption and then studies the impact of scheduling seven different popular applications over one to four cores on the overall power consumption. Based on this study, the paper proposes three new power-aware scheduling algorithms that dynamically schedule optimal number of cores as well as dynamically adjust the voltage frequency of each online core to achieve the best tradeoff between power consumption, application performance and user experience under the current context. Evaluation from a prototype implementation of the middleware on a quad-core HTC One shows that these algorithms result in significant reduction in power consumption while ensuring good performance and user experience

Deformation behavior of an electrodeposited nano-Ni/amorphous Fe78Si9B13 laminated composite sheet

A nano-Ni/amorphous Fe78Si9B13 composite sheet was prepared in the form of three-ply (Ni-Fe78Si9B13-Ni) laminated structure by an electrodeposition method. The average grain size of Ni layers is about 50 nm. The interface of laminated composite was investigated with SEM equipped with energy dispersive scanning (EDS) and line analysis technique. The laminated composite has a good interfacial bonding between amorphous layer and nano-Ni layers due to the mutual diffusion of atoms in Fe78Si9B13 and Ni layers during the process of electrodeposition. A maximum elongation of 115.5% was obtained when the volume fraction of nano-Ni layers (VNi) was 0.77, which is greatly higher than that of monolithic amorphous Fe78Si9B13 ribbon (36.3%) tested under the same conditions. Bulging tests were carried out to evaluate plastic forming properties of the Fe78Si9B13/Ni laminated composite. Under the condition of 450 °C, 4.0 MPa and 30 min, a good bulging part with the relative bulging height (RBH) of 0.4 was obtained

Deformation behavior of an electrodeposited nano-Ni/amorphous Fe

A nano-Ni/amorphous Fe78Si9B13 composite sheet was prepared in the form of three-ply (Ni-Fe78Si9B13-Ni) laminated structure by an electrodeposition method. The average grain size of Ni layers is about 50 nm. The interface of laminated composite was investigated with SEM equipped with energy dispersive scanning (EDS) and line analysis technique. The laminated composite has a good interfacial bonding between amorphous layer and nano-Ni layers due to the mutual diffusion of atoms in Fe78Si9B13 and Ni layers during the process of electrodeposition. A maximum elongation of 115.5% was obtained when the volume fraction of nano-Ni layers (VNi) was 0.77, which is greatly higher than that of monolithic amorphous Fe78Si9B13 ribbon (36.3%) tested under the same conditions. Bulging tests were carried out to evaluate plastic forming properties of the Fe78Si9B13/Ni laminated composite. Under the condition of 450 °C, 4.0 MPa and 30 min, a good bulging part with the relative bulging height (RBH) of 0.4 was obtained

Research on Dynamic Comprehensive Evaluation of Resource Allocation Efficiency of Technology Innovation in the Aerospace Industry

From the perspective of input and output, this paper constructs an evaluation index system for the status quo of technology innovation resource allocation in China’s aerospace industry. Taking the industrial panel data of 20 provincial regions from 2007 to 2016 in China as samples, this paper uses the stochastic frontier method, which is improved by the projection pursuit model based on accelerated genetic algorithm, to analyze the factors influencing the allocation efficiency of technology innovation resource in the aerospace industry and then make a static evaluation for the current situation. In addition, based on the perspective of velocity characteristics, this study uses the dynamic comprehensive evaluation model to evaluate the resource allocation of technology innovation in the aerospace industry. The empirical research shows that the resource allocation efficiency of technology innovation in the aerospace industry is generally at the lower middle level, indicating an unbalanced trend of “reverse” allocation with the level of regional economic development. It is also found that the efficiency improvement effect in recent years is not obvious. At last, based on the study’s findings, some countermeasures and suggestions are put forward to improve the current situation