Electric vehicle energy consumption modelling and estimation—A case study

Electric vehicles (EVs) have a limited driving range compared to conventional vehicles. Accurate estimation of EV's range is therefore a significant need to eliminate “range anxiety” that refers to drivers' fear of running out of energy while driving. However, the range estimators used in the currently available EVs are not sufficiently accurate. To overcome this issue, more accurate range estimation techniques are investigated. Nonetheless, an accurate power‐based EV energy consumption model is crucial to obtain a precise range estimation. This paper describes a study on EV energy consumption modelling. For this purpose, EV modelling is carried out using MATLAB/Simulink software based on a real EV in the market, the BMW i3. The EV model includes vehicle powertrain system and longitudinal vehicle dynamics. The powertrain is modelled using efficiency maps of the electric motor and the power electronics' data available for BMW i3. It also includes a transmission and a battery model (ie, Thevenin equivalent circuit model). A driver model is developed as well to control the vehicle's speed and to represent human driver's behaviour. In addition, a regenerative braking strategy, based on a series brake system, is developed to model the behaviour of a real braking controller. Auxiliary devices are also included in the EV model to improve energy consumption estimation accuracy as they can have a significant impact on that. The vehicle model is validated against published energy consumption values that demonstrates a satisfactory level of accuracy with 2% to 6% error between simulation and experimental results for Environmental Protection Agency and NEDC tests.     

F-OFDM仿真系统设计与时频同步算法

针对新一代5G波形的F-OFDM技术开展了研究,通过把一个宽带分为若干个子带,对每个子带进行滤波处理以实现更好的通信效能。基于Simulink平台进行了F-OFDM仿真系统的搭建,重点对F-OFDM符号同步方法和频偏估计方法进行了研究与仿真分析。实验结果表明,基于Chu序列相比采用PN序列可以获得更好的同步效果,基于导频的Classen频偏估计算法相比基于CP的CFO估计算法和基于训练序列的Moose估计方法可以获得更好的频偏估计效果。     

Effect of boron on the hydrogen-induced grain boundary embrittlement in α-Fe

The influence of interstitial impurities such as B and C on the H-induced Fe Σ5(310) symmetrical tilt grain boundary embrittlement was investigated using the projector augmented-wave method. It was shown that in contrast to hydrogen, both boron and carbon decrease the grain boundary energy more significantly than the surface one. This results in an increase in the Griffith work, i.e. the grain boundary strengthening. The strengthening of grain boundary is more pronounced with increased number of B atoms whereas the increase of H concentration makes the process of intergranular brittle cleavage fracture easier. The grain boundary energy is lowered with an increased number of B atoms indicating a strong driving force for segregation. Our estimations of the Griffith work for the Fe Σ5(310) grain boundary containing both B and H atoms show an increase in comparison with the undoped grain boundary. It is revealed that improved cohesion of Fe Σ5(310) grain boundary due to B is mainly a chemical effect, whereas both elastic and chemical contributions to the Griffith work in case of H are negative, i.e. they are embrittling contributions.     

Hydrogen related degradation in pipeline steel: A review

To support our increasing energy demand, steel pipelines are deployed in transporting oil and natural gas resources for long distances. However, numerous steel structures experience catastrophic failures due to the evolution of hydrogen from their service environments initiated by corrosion reactions and/or cathodic protection. This process results in deleterious effect on the mechanical strength of these ferrous steel structures and their principal components. The major sources of hydrogen in offshore/subsea pipeline installations are moisture as well as molecular water reduction resulting from cathodic protection. Hydrogen induced cracking comes into effect as a synergy of hydrogen concentration and stress level on susceptible steel materials, leading to severe hydrogen embrittlement (HE) scenarios. This usually manifests in the form of induced-crack episodes, e.g., hydrogen induced cracking (HIC), stress-oriented hydrogen induced cracking (SOHIC) and sulfide stress corrosion cracking (SSCC). In this work, we have outlined sources of hydrogen attack as well as their induced failure mechanisms. Several past and recent studies supporting them have also been highlighted in line with understanding of the effect of hydrogen on pipeline steel failure. Different experimental techniques such as Devanathan–Stachurski method, thermal desorption spectrometry, hydrogen microprint technique, electrochemical impedance spectroscopy and electrochemical noise have proven to be useful in investigating hydrogen damage in pipeline steels. This has also necessitated our coverage of relatively comprehensive assessments of the effect of hydrogen on contemporary high-strength pipeline steel processed by thermomechanical controlled rolling. The effect of HE on cleavage planes and/or grain boundaries has prompted in depth crystallographic texture analysis within this work as a very important parameter influencing the corrosion behavior of pipeline steels. More information regarding microstructure and grain boundary interaction effects have been presented as well as the mechanisms of crack interaction with microstructure. Since hydrogen degradation is accompanied by other corrosion-related causes, this review also addresses key corrosion causes affecting offshore pipeline structures fabricated from steel. We have enlisted and extensively discussed several recent corrosion mitigation trials and performance tests in various media at different thermal and pressure conditions.     

Influence of the grain structure of yttria thin films on the hydrogen isotope permeation

Steel components are required in the infrastructure and the facilities of the hydrogen economy. The high hydrogen pressures in the hydrogen economy lead to embrittlement and surface corrosion of the steels. For the functionality of the facilities it is necessary to suppress the embrittlement and the surface corrosion of the steels by protective layers, e.g. ceramic thin films. With regard to fusion power plants ceramic thin films on the structural steel materials are also required. These thin films work as a tritium permeation barrier that is necessary to prevent the loss of the radioactive fuel inventory. Oxide thin films, e.g. Al₂O₃, Er₂O₃, and Y₂O₃, are promising candidates as tritium permeation barrier layers. In terms of the application in the first wall, this is especially true for yttrium due to its favorably short decay time after neutron activation compared to the other candidates. The Y₂O₃ layers with thicknesses of 0.5 μm–1 μm are deposited on both substrate sides by RF magnetron sputter deposition. Since the microstructure of the barrier layer plays an important role for the permeation reduction, layers with three different magnetron process modes and thus three different microstructures are prepared. After annealing the cubic crystal structure of all thin films is verified by X-ray diffraction and the different microstructures are investigated by scanning electron microscopy and transmission electron microscopy. The Y₂O₃ stoichiometry of all thin films and a chromium oxide material segregation at the interface are verified by analysis methods such as X-ray photoelectron spectroscopy. The permeation reduction factors of all thin films are determined in gas-driven deuterium permeation experiments. Corresponding to the three different microstructures, reduction factors of 25, 45, and 1100 are identified. Thus, the permeation reduction is strongly dependent on the Y₂O₃ microstructure. The measurement results suggest that a high density of grain boundaries leads to a high hydrogen permeation.     

自适应SA-PSO优化的威布尔混合分布参数估计方法及应用

针对采用传统参数估计方法得到的模型拟合误差较大的问题，建立多重威布尔混合分布参数估计的非线性最小二乘模型，并提出基于模拟退火（SA）思想的自适应粒子群（PSO）算法进行求解。在PSO算法优化过程中，采用自适应方法调整惯性权重和加速因子，加快其收敛速度；引入模拟退火机制，根据Metropolis准则确定最优粒子的取舍，改善其全局搜索能力。将该方法应用到某型柴油机喷油器失效分布的参数估计中，并与图解法、基于Levenberg-Marquardt的非线性最小二乘法、标准PSO算法、自适应PSO算法求解的结果进行比较，分析所提方法的优化性能及精度。结果表明，该方法能够有效提高多重威布尔混合分布模型参数估计的精度和效率。     

基于广义二次互相关的低信噪比信号时延估计

针对时延估计精度受噪声影响,导致时延估计不准确的问题,在现有广义二次相关算法的基础上,提出了一种改进的广义二次相关算法,通过将二次相关函数先做指数运算,降低噪声干扰,再将傅里叶逆变换得到的相关函数做高次方运算,达到锐化峰值提高时延正确率的目的。仿真结果表明,信噪比(SNR)在0~10 dB时,改进算法的均方根误差明显优于广义二次相关算法,正确率相比于广义二次相关算法也显著提高,且在更低SNR的情况下仍然具有一定优势。     

Backtesting portfolio value-at-risk with estimated portfolio weights

This article theoretically and empirically analyzes backtesting portfolio value-at-risk (VaR) with estimation risk in an intrinsically multi-variate framework. It particularly takes into account the estimation of portfolio weights in forecasting portfolio VaR and its impact on backtesting. It shows that the estimation risk from estimating portfolio weights and that from estimating the multi-variate dynamic model make the existing methods in a univariate framework inapplicable. It proposes a general theory to quantify estimation risk applicable to the present problem and suggests practitioners a simple but effective way to implement valid inference to overcome the effect of estimation risk in backtesting portfolio VaR. In particular, we apply our theory to the efficient mean-variance-skewness portfolio for a multi-variate generalized autoregressive conditional heteroscedasticity model with multi-variate general hyperbolic distributed innovations. Some Monte Carlo simulations and an empirical application demonstrate the merits of our method.