Compounding factors and their effect on the design of long range battery electric vehicles

 It is well known that the one of the main problems concerning battery electric vehicles (BEVs) is their short range compared to conventional petrol and diesel vehicles. In this work the technical factors that will enable long range BEVs are investigated. The concept of Compounding Factors is presented and shows that if certain parameters can be met then BEV’s can have a comparable performance to conventional petrol cars. The development and initial testing of a long range BEW prototype is presented and discussed.

Power-cycle-library-based control strategy for plug-in hybrid electric vehicles

It has been demonstrated that considering the knowledge of drive cycle as a priori in the PHEV control strategy can improve its performance. The concept of power cycle instead of drive cycle is introduced to consider the effect of noise factors in the prediction of future drivetrain power demand. To minimize the effect of noise factors, a practical solution for developing a power-cycle library is introduced. A control strategy is developed using the predicted power cycle which inherently improves the optimal operation of engine and consequently improves the vehicle performance. Since the control strategy is formed exclusively for each PHEV rather than a preset strategy which is designed by OEM, the effect of different environmental and geographic conditions, driver behavior, aging of battery and other components are considered for each PHEV. Simulation results show that the control strategy based on the driver library of power cycle would improve both vehicle performance and battery health.

Effects of electric fields on pollen rupture

RATIONALE: To determine whether the potential for previous termpollennext term fragmentation is increased during thunderstorms by exploring the previous termeffectsnext term of previous termelectricnext termprevious termfieldsnext term, with magnitude as found in the outdoor environment.

METHODS: Fresh previous termpollennext term grains were collected from bermudagrass flowers. A light microscope was modified with the addition of an previous termelectricnext termprevious termfieldnext term generated from a DC source (0-20 V) that was applied to the stage. Water was added to test for previous termpollennext termprevious termrupturenext term and to assess previous termpollennext term viability.

RESULTS: Bermuda grass previous termpollennext term did not previous termrupturenext term within 1 h of contact with water. Only after exposure to an previous termelectricnext termprevious termfieldnext term did Bermudagrass previous termpollennext term show a considerable amount of rupturing immediately upon immersion in water. The higher the voltage the previous termpollennext term is exposed to before coming into contact with water, the higher the percentage of previous termrupturenext term of the previous termpollennext term. previous termElectricnext termprevious termfieldsnext term, generated in the laboratory and of magnitude found during thunderstorms, affected the previous termpollennext term after as little as a 5 s exposure. The highest percentage of previous termrupturenext term occurred after exposures of at least 10 s: 80% previous termrupturenext term occurred after 10 s exposure at 10kVolts/m. This previous termeffectnext term is sustained for at least 15 min.

CONCLUSIONS: Thunderstorm regularly generate previous termelectricnext termprevious termfieldsnext term up to 5 kV/m in strength, and can reach 10kV/m, and cover several km in distance. The magnitude of the previous termelectricnext termprevious termfieldsnext term that affects the previous termpollennext term grains in the laboratory is low enough to be commonly found in the outdoor environment during thunderstorms. These previous termelectricnext termprevious termfields prime previous termpollen grains for more rapid release of allergenic particles.

Plane wave scattering by a spherical di-electric particle in motion : a relativistic extension of the Mie theory

Light scattering from small spherical particles has applications in a vast number of disciplines including astrophysics, meteorology optics and particle sizing. Mie theory provides an exact analytical characterization of plane wave scattering from spherical dielectric objects. There exist many variants of the Mie theory where fundamental assumptions of the theory has been relaxed to make generalizations. Notable such extensions are generalized Mie theory where plane waves are replaced by optical beams, scattering from lossy particles, scattering from layered particles or shells and scattering of partially coherent (non-classical) light. However, no work has yet been reported in the literature on modifications required to account for scattering when the particle or the source is in motion relative to each other. This is an important problem where many applications can be found in disciplines involving moving particle size characterization. In this paper we propose a novel approach, using special relativity, to address this problem by extending the standard Mie theory for scattering by a particle in motion with a constant speed, which may be very low, moderate or comparable to the speed of light. The proposed technique involves transforming the scattering problem to a reference frame co-moving with the particle, then applying the Mie theory in that frame and transforming the scattered field back to the reference frame of the observer.

Look-ahead intelligent energy management of a parallel hybrid electric vehicle

Improving fuel efficiency in vehicles can reduce the energy consumption concerns associated with operating the vehicles. This paper presents a model for a parallel hybrid electric vehicle. In the model, the flow of energy starts from wheels and spreads toward engine and electric motor. A fuzzy logic based control strategy is implemented for the vehicle. The controller manages the energy flow from the engine and the electric motor, controlling transmission ratio, adjusting speed, and sustaining battery's state of charge. The controller examines the vehicle speed, demand torque, slope difference, state of charge of battery, and engine and electric motor rotation speeds. It then determines the best values for continuous variable transmission ratio, speed, and torque. A slope window method is formed that takes into account the look-ahead slope information, and determines the best vehicle speed. The developed model and control strategy are simulated using real highway data relating to Nowra-Bateman Bay in Australia, and SAE Highway Fuel Economy Driving Schedule. The simulation results are presented and discussed. It is shown that the use of the proposed fuzzy controller reduces the fuel consumption of the vehicle.

Direct method for optimal power management in hybrid electric vehicles

Hybrid electric vehicles are powered by an electric system and an internal combustion engine. The components of a hybrid electric vehicle need to be coordinated in an optimal manner to deliver the desired performance. This paper presents an approach based on direct method for optimal power management in hybrid electric vehicles with inequality constraints. The approach consists of reducing the optimal control problem to a set of algebraic equations by approximating the state variable which is the energy of electric storage, and the control variable which is the power of fuel consumption. This approximation uses orthogonal functions with unknown coefficients. In addition, the inequality constraints are converted to equal constraints. The advantage of the developed method is that its computational complexity is less than that of dynamic and non-linear programming approaches. Also, to use dynamic or non-linear programming, the problem should be discretized resulting in the loss of optimization accuracy. The propsed method, on the other hand, does not require the discretization of the problem producing more accurate results. An example is solved to demonstrate the accuracy of the proposed approach. The results of Haar wavelets, and Chebyshev and Legendre polynomials are presented and discussed. © 2011 The Korean Society of Automotive Engineers and Springer-Verlag Berlin Heidelberg.

Effect of noise factors in energy management of series plug-in hybrid electric vehicles

It has been demonstrated that charge depletion (CD) energy management strategies are more efficient choices for energy management of plug-in hybrid electric vehicles (PHEVs). The knowledge of drive cycle as a priori can improve the performance of CD energy management in PHEVs. However, there are many noise factors which affect both drivetrain power demand and vehicle performance even in identical drive cycles. In this research, the effect of each noise factor is investigated by introducing the concept of power cycle instead of drive cycle for a journey. Based on the nature of the noise factors, a practical solution for developing a power-cycle library is introduced. Investigating the predicted power cycle, an energy management strategy is developed which considers the influence of temperature noise factor on engine performance. The effect of different environmental and geographic conditions, driver behavior, aging of battery and other components are considered. Simulation results for a modelled series PHEV similar to GM Volt show that the suggested energy management strategy based on the driver power cycle library improves both vehicle fuel economy and battery health by reducing battery load and temperature.

Shear-free perfect fluids with a solenoidal electric curvature

We prove that the vorticity or the expansion vanishes for any shear-free perfect fluid solution of the Einstein field equations where the pressure satisfies a barotropic equation of state and the spatial divergence of the electric part of the Weyl tensor is zero.

Intelligent energy management for plug-in hybrid electric vehicles : the role of ITS infrastructure in vehicle electrification

The desire to reduce carbon emissions due to transportation sources has led over the past decade to the development of new propulsion technologies, focused on vehicle electrification (including hybrid, plug-in hybrid and battery electric vehicles). These propulsion technologies, along with advances in telecommunication and computing power, have the potential of making passenger and commercial vehicles more energy efficient and environment friendly. In particular, energy management algorithms are an integral part of plug-in vehicles and are very important for achieving the performance benefits. The optimal performance of energy management algorithms depends strongly on the ability to forecast energy demand from the vehicle. Information available about environment (temperature, humidity, wind, road grade, etc.) and traffic (traffic density, traffic lights, etc.), is very important in operating a vehicle at optimal efficiency. This article outlines some current technologies that can help achieving this optimum efficiency goal. In addition to information available from telematic and geographical information systems, knowledge of projected vehicle charging demand on the power grid is necessary to build an intelligent energy management controller for future plug-in hybrid and electric vehicles. The impact of charging millions of vehicles from the power grid could be significant, in the form of increased loading of power plants, transmission and distribution lines, emissions and economics (information are given and discussed for the US case). Therefore, this effect should be considered in an intelligent way by controlling/scheduling the charging through a communication based distributed control.

Electric field analysis of spinneret design for needleless electrospinning of nanofibers

Concentrated electric field is crucial in generation of needleless electrospinning; the electric field profile together with electric field intensity of the spinneret directly affect the needleless electrospinning performance. Understanding the electric field of different spinnerets would definitely benefit the design and optimization of needleless electrospinning. Three-dimensional (3D) finite element analysis has been used to analyze the electric field profile and electric field intensity of different spinnerets for needleless electrospinning by using the simulation software COMSOL Multiphysics 3.5a. It has been found that evolution of the spinneret of needleless electrospinning from cylinder to multiple disks and then to multiple rings results in stronger and more concentrated electric field. The analysis based on 3D simulation of the electric field could benefit further development of needleless electrospinning in which the production rate and quality of as-spun nanofibers are of great importance.

Comparative study on MoO3 and HxMoO3 nanobelts : structure and electric transport

In this study, the suspension of MoO3 nanobelts was first prepared in a hydrothermal way from Mo powders and H2O2 solution, which could be transformed into the suspension of HxMoO3 nanobelts under an acidic condition using N2H4 ·H2O as the reducing agent. Three paper-form samples made from MoO3 and HxMoO3 nanobelts (low or high hydrogen content) were then fabricated via a vacuum filtration method, followed by their structural comparative analysis such as FESEM, XRD, Raman spectra, and XPS, etc. The measurement of electric resistances at room temperature shows that the conductance of HxMoO3 nanobelts is greatly improved because of hydrogen doping. The temperature-dependent resistances of HxMoO3 nanobelts agree with the exponential correlation, supporting that the conducting carriers are the quasi-free electrons released from Mo5+. In addition, the formation process of HxMoO3 nanobelts from MoO3 nanobelts is also discussed.