Monitoring energy usage of heavy-haul iron ore trains with on-board energy meter for improving energy efficiency

Purpose-For billing purposes,heavy-haul locomotives in Sweden are equipped with on-board energy meters,which can record several parameters,e.g.,used energy,regenerated energy,speed and position.Since there is a strong demand for improving energy efficiency in Sweden,data from the energy meters can be used to obtain a better understanding of the detailed energy usage of heavy-haul trains and identify potential for future improvements.Design/methodology/approach-To monitor energy efficiency,the present study,therefore,develops key performance indicators(KPIs),which can be calculated with energy meter data to reflect the energy efficiency of heavy-haul trains in operation.Energy meter data of IORE class locomotives,hauling highly uniform 30-tonne axle load trains with 68 wagons,together with additional data sources,are analysed to identify significant parameters for describing driver influence on energy usage.Findings-Results show that driver behaviour varies significantly and has the single largest influence on energy usage.Furthermore,parametric studies are performed with help of simulation to identify the influence of different operational and rolling stock conditions,e.g.,axle loads and number of wagons,on energy usage.Originality/value-Based on the parametric studies,some operational parameters which have significant impact on energy efficiency are found and then the KPIs are derived.In the end,some possible measures for improving energy performance in heavy-haul operations are given.

Partial Iterative Decode of Turbo Codes for On-Board Processing Satellite Platform

There is a contradiction between high processing complexity and limited processing resources when turbo codes are used on the on-board processing(OBP)satellite platform.To solve this problem,this paper proposes a partial iterative decode method for on-board application,in which satellite only carries out limited number of iteration according to the on-board processing resource limitation and the throughput capacity requirements.In this method,the soft information of parity bits,which is not obtained individually in conventional turbo decoder,is encoded and forwarded along with those of information bits.To save downlink transmit power,the soft information is limited and normalized before forwarding.The iteration number and limiter parameters are optimized with the help of EXIT chart and numerical analysis,respectively.Simulation results show that the proposed method can effectively decrease the complexity of onboard processing while achieve most of the decoding gain..

Role of on-board discharge in shock wave drag reduction and plasma cloaking

In the present paper, a physical model is proposed for reducing the problem of the drag reduction of an attached bow shock around the nose of a high-speed vehicle with on-board discharge, to the problem of a balance between the magnetic pressure and gas pressure of plane shock of a partially ionized gas consisting of the environmental gas around the nose of the vehicle and the on-board discharge-produced plasma. The relation between the shock strength and the discharge-induced magnetic pressure is studied by means of a set of one-fluid, hydromagnetic equations reformed for the present purpose, where the discharge-induced magnetic field consists of the electron current （produced by the discharge）-induced magnetic field and the partially ionized gas flow-induced one. A formula for the relation between the above parameters is derived. It shows that the discharge-induced magnetic pressure can minimize the shock strength, successfully explaining the two recent experimental observations on attached bow shock mitigation and elimination in a supersonic flow during on-board discharge [Phys. Plasmas 9 （2002） 721 and Phys. Plasmas 7 （2000） 1345]. In addition, the formula implies that the shock elimination leaves room for a layer of higher-density plasma rampart moving around the nose of the vehicle, being favourable to the plasma radar cloaking of the vehicle. The reason for it is expounded.

Optimal energy saving in DC railway system withon-board energy storage system by using peak demand cutting strategy

A problem of peak power in DC-electrified railway systems is mainly caused by train power demand during acceleration.If this power is reduced,substation peak power will be significantly decreased.This paper presents a study on optimal energy saving in DC-electrified railway with on-board energy storage system(OBESS) by using peak demand cutting strategy under different trip time controls.The proposed strategy uses OBESS to store recovered braking energy and find an appropriated time to deliver the stored energy back to the power network in such a way that peak power of every substations is reduced.Bangkok Mass Transit System(BTS)-Silom Line in Thailand is used to test and verify the proposed strategy.The results show that substation peak power is reduced by63.49% and net energy consumption is reduced by 15.56%using coasting and deceleration trip time control.

Stream-computing of High Accuracy On-board Real-time Cloud Detection for High Resolution Optical Satellite Imagery

This paper focuses on the time efficiency for machine vision and intelligent photogrammetry, especially high accuracy on-board real-time cloud detection method. With the development of technology, the data acquisition ability is growing continuously and the volume of raw data is increasing explosively. Meanwhile, because of the higher requirement of data accuracy, the computation load is also becoming heavier. This situation makes time efficiency extremely important. Moreover, the cloud cover rate of optical satellite imagery is up to approximately 50%, which is seriously restricting the applications of on-board intelligent photogrammetry services. To meet the on-board cloud detection requirements and offer valid input data to subsequent processing, this paper presents a stream-computing of high accuracy on-board real-time cloud detection solution which follows the “bottom-up” understanding strategy of machine vision and uses multiple embedded GPU with significant potential to be applied on-board. Without external memory, the data parallel pipeline system based on multiple processing modules of this solution could afford the “stream-in, processing, stream-out” real-time stream computing. In experiments, images of GF-2 satellite are used to validate the accuracy and performance of this approach, and the experimental results show that this solution could not only bring up cloud detection accuracy, but also match the on-board real-time processing requirements.

Radiation Tolerant Viterbi Decoders for On-Board Processing(OBP) in Satellite Communications

Modern satellite communication systems require on-board processing(OBP)for performance improvements,and SRAM-FPGAs are an attractive option for OBP implementation.However,SRAM-FPGAs are sensitive to radiation effects,among which single event upsets(SEUs)are important as they can lead to data corruption and system failure.This paper studies the fault tolerance capability of a SRAM-FPGA implemented Viterbi decoder to SEUs on the user memory.Analysis and fault injection experiments are conducted to verify that over 97%of the SEUs on user memory would not lead to output errors.To achieve a better reliability,selective protection schemes are then proposed to further improve the reliability of the decoder to SEUs on user memory with very small overhead.Although the results are obtained for a specific FPGA implementation,the developed reliability estimation model and the general conclusions still hold for other implementations.

Novel satellite transport protocol with on-board spoofing proxy

As a result of the exponential growing rate of worldwide Internet usage, satellite systems are required to support broadband Internet applications. The transmission control protocol （TCP） which is widely used in the Internet, performs very well on wired networks. However, in the case of satellite channels, clue to the delay and transmission errors, TCP performance degrades significantly and bandwidth of satellite links can not be fully utilized. To improve the TCP performance, a new idea of placing a TCP spoofing proxy in the satellite is considered. A Novel Satellite Transport Protocol （NSTP） which takes advantage of the special properties of the satellite channel is also proposed. By using simulation, as compared with traditional TCPs, the on-board spoofing proxy integrated with the special transport protocol can significantly enhance throughput performance on the high BER satellite link, the time needed to transfer files and the bandwidth used in reverse path are sharply reduced.

Adaptive Constrained On-board Guidance Technology forPowered Glide Vehicle

To make full use of expanded maneuverability and increased range,adaptive constrained on-board guidance technology is the key capability for a glide vehicle with a double-pulse rocket engine,especially under the requirements of desired target changing and on-line reconfigurable control and guidance.Based on the rapid footprint analysis,whether the new target is within the current footprint area is firstly judged.If not,the rocket engine ignites by the logic obtained from the analysis of optimal flight range by the method of hp-adaptive Gauss pseudospectral method(hp-GPM).Then,an on-board trajectory generation method based on powered quasi-equilibrium glide condition(QEGC)and linear quadratic regulator(LQR)method is used to guide the vehicle to the new target.The effectiveness of the guidance method consisted of powered on-board trajectory generation,LQR trajectory tracking,footprint calculation,and ignition time determination is indicated by some simulation examples.

Thermodynamic Aspects of the Graphene/Graphane/Hydrogen Systems: Relevance to the Hydrogen On-Board Storage Problem

The present analytical review is devoted to the current problem of thermodynamic stability and related thermodynamic characteristics of the following graphene layers systems: 1) double-side hydrogenated graphene of composition CH (theoretical graphane) (Sofo et al. 2007) and experimental graphane (Elias et al. 2009);2) theoretical single-side hydrogenated graphene of composition CH;3) theoretical single-side hydrogenated graphene of composition C2H (graphone);4) experimental hydrogenated epitaxial graphene, bilayer graphene and a few layers of graphene on SiO2 or other substrates;5) experimental and theoretical single-external side hydrogenated single-walled carbon nanotubes, and experimental hydrofullerene C60H36;6) experimental single-internal side hydrogenated (up to C2H or CH composition) graphene nanoblisters with intercalated high pressure H2 gas inside them, formed on a surface of highly oriented pyrolytic graphite or epitaxial graphene under the atomic hydrogen treatment;and 7) experimental hydrogenated graphite nanofibers-multigraphene with intercalated solid H2 nano-regions of high density inside them, relevant to solving the problem of hydrogen on-board storage (Nechaev 2011-2012).

Comparing of Hydrogen On-Board Storage by the Largest Car Companies, Relevance to Prospects for More Efficient Technologies

It presented a comparative consideration of General Motors long-term activities on the current subject of fuel-cell-powered electric vehicles vs Toyota Mirai recent results, relevant to prospects on more efficient and safe technologies of the hydrogen on-board storage. It also presented a call on the project International cooperation. The main aim of this paper is to attract attention of General Motors, Toyota and/or other large car companies to a real possibility of developing and using, in the nearest future, of the break-through hydrogen on-board storage technology based on the solid H2 intercalation into graphite nanostructures.

Nanostructuring of Mg-Based Hydrogen Storage Materials:Recent Advances for Promoting Key Applications

With the depletion of fossil fuels and global warming,there is an urgent demand to seek green,low-cost,and high-efficiency energy resources.Hydrogen has been considered as a potential candidate to replace fossil fuels,due to its high gravimetric energy density(142 MJ kg^(-1)),high abundance(H_(2)O),and environmentalfriendliness.However,due to its low volume density,effective and safe hydrogen storage techniques are now becoming the bottleneck for the"hydrogen economy".Under such a circumstance,Mg-based hydrogen storage materials garnered tremendous interests due to their high hydrogen storage capacity(~7.6 wt%for MgH_(2)),low cost,and excellent reversibility.However,the high thermodynamic stability(ΔH=-74.7 kJ mol^(-1)H_(2))and sluggish kinetics result in a relatively high desorption temperature(>300℃),which severely restricts widespread applications of MgH_(2).Nano-structuring has been proven to be an effective strategy that can simultaneously enhance the ab/de-sorption thermodynamic and kinetic properties of MgH_(2),possibly meeting the demand for rapid hydrogen desorption,economic viability,and effective thermal management in practical applications.Herein,the fundamental theories,recent advances,and practical applications of the nanostructured Mg-based hydrogen storage materials are discussed.The synthetic strategies are classified into four categories:free-standing nano-sized Mg/MgH_(2)through electrochemical/vapor-transport/ultrasonic methods,nanostructured Mg-based composites via mechanical milling methods,construction of core-shell nano-structured Mg-based composites by chemical reduction approaches,and multi-dimensional nano-sized Mg-based heterostructure by nanoconfinement strategy.Through applying these strategies,near room temperature ab/de-sorption(<100℃)with considerable high capacity(>6 wt%)has been achieved in nano Mg/MgH_(2)systems.Some perspectives on the future research and development of nanostructured hydrogen storage materials are also provided.

Progress in reentry trajectory planning for hypersonic vehicle

The reentry trajectory planning for hypersonic vehicles is critical and challenging in the presence of numerous nonlinear equations of motion and path constraints, as well as guaranteed satisfaction of accuracy in meeting all the specified boundary conditions. In the last ten years, many researchers have investigated various strategies to generate a feasible or optimal constrained reentry trajectory for hypersonic vehicles. This paper briefly reviews the new research efforts to promote the capability of reentry trajectory planning. The progress of the onboard reentry trajectory planning, reentry trajectory optimization, and landing footprint is summarized. The main challenges of reentry trajectory planning for hypersonic vehicles are analyzed, focusing on the rapid reentry trajectory optimization, complex geographic constraints, and coop- erative strategies.

Application of multi-outputs LSSVR by PSO to the aero-engine model

Considering the modeling errors of on-board self-tuning model in the fault diagnosis of aero-engine, a new mechanism for compensating the model outputs is proposed. A discrete series predictor based on multi-outputs least square support vector regression （LSSVR） is applied to the compensation of on-board self-tuning model of aero-engine, and particle swarm optimization （PSO） is used to the kernels selection of multi-outputs LSSVR. The method need not reconstruct the model of aero-engine because of the differences in the individuals of the same type engines and engine degradation after use. The concrete steps for the application of the method are given, and the simulation results show the effectiveness of the algorithm.

Robustness Assessment and Adaptive FDI for Car Engine

A new on-line fault detection and isolation （FDI） scheme proposed for engines using an adaptive neural network classifier is evaluated for a wide range of operational modes to check the robustness of the scheme in this paper. The neural classifier is adaptive to cope with the significant parameter uncertainty, disturbances, and environment changes. The developed scheme is capable of diagnosing faults in on-line mode and the FDI for the closed-loop system with can be directly implemented in an on-board crankshaft speed feedback is investigated by diagnosis system （hardware）. The robustness of testing it for a wide range of operational modes including robustness against fixed and sinusoidal throttle angle inputs, change in load, change in an engine parameter, and all these changes occurring at the same time. The evaluations are performed using a mean value engine model （MVEM）, which is a widely used benchmark model for engine control system and FDI system design. The simulation results confirm the robustness of the proposed method for various uncertainties and disturbances.

Zeolites for Sensors for Reducing Gases

Due to their unique properties,zeolites can be used either as passive filters to greatly enhance selectivity or as very selective sensor materials.Some well known principles are briefly reviewed and the following three novel application modes are discussed.Zeolites can be applied as cover layers for specificity improvement of p-type semiconducting hydrocarbon sensors.Furthermore,a novel combination of metal oxides with zeolites leading to a very selective hydrocarbon sensor is described.In this application,it is shown that the interface chromium oxide/zeolite plays an essential role.And,in a very recent approach,Na^+ ion conducting zeolites are applied as an auxiliary phase in a potentiometric gas sensor.The cell voltage shows a Nernstian response,which is selective towards propane.Here,the proposed mechanism assumes Na^+ activity changes in the zeolite pores due to hydrocarbon sorption.

Strain Measurement for Hollow Projectiles During Its Penetration of Concrete Targets

Gives a new technique to measure the dynamic deformation behavior and strain development of a hollow steel projectile during its penetration of concrete targets. Direct strain measurement was performed by applying strain gages attached to the inner walls of the hollow projectile, linked with on-board testing and storage recorder. This on-board test-record system is easy to operate, cost-effective and can provide reasonable, accurate and detailed information. Obverse ballistic experiments were carried out on ogival-nose hollow projectiles normally impacting concrete targets at velocities from 150 m/s to 300 m/s. The deformation process of projectiles was measured, recorded and played back. Profiles of voltage-time relationship were successively obtained and transfered to strain-time relationship with the aid of calibration tables. It was found that projectiles go through a series of compression and tension deformations intermittently. Relationships between strain development and projectile deformation process were discussed.

An optimized run-length based algorithm for sparse remote sensing image labeling

Labeling of the connected components is the key operation of the target recognition and segmentation in remote sensing images.The conventional connected-component labeling(CCL) algorithms for ordinary optical images are considered time-consuming in processing the remote sensing images because of the larger size.A dynamic run-length based CCL algorithm(Dy RLC) is proposed in this paper for the large size,big granularity sparse remote sensing image,such as space debris images and ship images.In addition,the equivalence matrix method is proposed to help design the pre-processing method to accelerate the equivalence labels resolving.The result shows our algorithm outperforms 22.86% on execution time than the other algorithms in space debris image dataset.The proposed algorithm also can be implemented on the field programming logical array(FPGA) to enable the realization of the real-time processing on-board.

TinyML-Based Fall Detection for Connected Personal Mobility Vehicles

A new wave of electric vehicles for personal mobility is currently crowding public spaces.They offer a sustainable and efficient way of getting around in urban environments,however,these devices bring additional safety issues,including serious accidents for riders.Thereby,taking advantage of a connected personal mobility vehicle,we present a novel on-device Machine Learning(ML)-based fall detection system that analyzes data captured from a range of sensors integrated on an on-board unit(OBU)prototype.Given the typical processing limitations of these elements,we exploit the potential of the TinyML paradigm,which enables embedding powerful ML algorithms in constrained units.We have generated and publicly released a large dataset,including real riding measurements and realistically simulated falling events,which has been employed to produce different TinyML models.The attained results show the good operation of the system to detect falls efficiently using embedded OBUs.The considered algorithms have been successfully tested on mass-market low-power units,implying reduced energy consumption,flash footprints and running times,enabling new possibilities for this kind of vehicles.

Adaptive Sliding Mode Control Method for Onboard Supercapacitors System

Urban rail trains have undergone rapid development in recent years due to their punctuality,high capacity and energy efficiency.Urban trains require frequent start/stop operations and are,therefore,prone to high energy losses.As trains have high inertia,the energy that can be recovered from braking comes in short bursts of high power.To effectively recover such braking energy,an onboard supercapacitor system based on a radial basis function neural networkbased sliding mode control system is proposed,which provides robust adaptive performance.The supercapacitor energy storage system is connected to a bidirectional DC/DC converter to provide traction energy or absorb regenerative braking energy.In the Boost and Buck modes,the state-space averaging method is used to establish a model and perform exact linearization.An adaptive sliding mode controller is designed,and simulation results show that it can effectively solve the problems of low energy utilization and large voltage fluctuations in urban rail electricity grids,and maximise the recovery and utilization of regenerative braking energy.

Statistical Model for Estimating Carbon Dioxide Emissions from a Light-Duty Gasoline Vehicle

The objective of this research was development of a statistical model for estimating vehicle tailpipe emissions of carbon dioxide (CO2). Forty hours of second-by-second emissions data (144,000 data points) were collected using an On-Board emissions measurement System (Horiba OBS-1300) installed in a 2007 Dodge Charger car. Data were collected for two roadway types, arterial and highway, around Arlington, Texas, and two different time periods, off peak and peak (both a.m. and p.m.). Multiple linear regression and SAS software were used to build emission models from the data, using predictor variables of velocity, acceleration and an interaction term. The arterial model explained 61% of the variability in the emissions;the highway model explained 27%. The arterial model in particular represents a reasonably good compromise between accuracy and ease of use. The arterial model could be coupled with velocity and acceleration profiles obtained from a micro-scale traffic simulation model, such as CORSIM, or from field data from an instrumented vehicle, to estimate percent emission reductions associated with local changes in traffic system operation or management.