Structural analysis based sensors fault detection and isolation of cylindrical lithium-ion batteries in automotive applications

The battery sensors fault diagnosis is of great importance to guarantee the battery performance, safety and life as the operations of battery management system (BMS) mainly depend on the embedded current, voltage and temperature sensor measurements. This paper presents a systematic model-based fault diagnosis scheme to detect and isolate the current, voltage and temperature sensor fault. The proposed scheme relies on the sequential residual generation using structural analysis theory and statistical inference residual evaluation. Structural analysis handles the pre-analysis of sensor fault detectability and isolability possibilities without the accurate knowledge of battery parameters, which is useful in the early design stages of diagnostic system. It also helps to find the analytical redundancy part of the battery model, from which subsets of equations are extracted and selected to construct diagnostic tests. With the help of state observes and other advanced techniques, these tests are ensured to be efficient by taking care of the inaccurate initial State-of-Charge (SoC) and derivation of variables. The residuals generated from diagnostic tests are further evaluated by a statistical inference method to make a reliable diagnostic decision. Finally, the proposed diagnostic scheme is experimentally validated and some experimental results are presented.     

四轮轮毂电机驱动电动汽车电液复合制动平顺性控制策略

液压制动与电机再生制动的时域响应差异导致电动汽车在制动模式切换时产生冲击感,影响驾驶员驾驶感受和乘坐舒适性。以四轮轮毂电机驱动电动汽车为研究对象,提出一种基于分层架构的电液复合制动平顺性控制策略。针对"高压蓄能器+电机泵"式电子液压制动系统（EHB）,上层控制器提出基于模糊控制的轮缸压力控制策略;针对制动模式切换过程中产生的冲击,下层控制器提出包括液压介入预测模块和电机制动补偿模块的电液复合制动平顺性控制策略。通过Simulink-AMESim联合仿真平台进行仿真试验验证。结果表明,轮缸压力控制策略能够保证轮缸液压力较好地追随目标压力,且稳态误差不超过2%;电液复合制动平顺性控制策略能够有效提高制动系统的响应速度,同时显著降低制动模式切换时的冲击,能提升车辆制动平顺性和乘坐舒适性。     

An energy matching method for battery electric vehicle and hydrogen fuel cell vehicle based on source energy consumption rate

The smart cities development requires reducing energy consumption and using as much renewable energy as possible, so the widespread use of new energy vehicles is a very important measure. In this work, for the energy system configuration and energy efficiency balance of new energy vehicles, we propose an energy matching method to study its energy efficiency from the view point for energy life cycle. Nowadays, new energy vehicles mainly include battery electric vehicles (BEV) and hydrogen fuel cell vehicles (HFCEV). Firstly, we proposed the Source to Range (STR) model. Then, based on STR model, we used energy efficiency analysis chart to visually represent the conversion, delivery and consumption of the vehicle energy life cycle. Furthermore, we proposed a Source Energy Consumption Rate (SECR), which is used to evaluate the vehicles energy efficiency. Finally, based on STR model, we obtained the dividing line of the same SECR for new energy vehicles and equivalent fuel vehicles, which provides constraints on the vehicle energy system design. The results show that STR model can provide an effective tool for energy matching and energy efficiency analysis of new energy vehicles, and has a reference for product development of new energy vehicles.     

Effective control of the microstructure of carbide-derived carbon by ball-milling the carbide precursor

A microstructure control strategy for carbide-derived carbon (CDC) by ball-milling the metal carbide precursor prior to CDC synthesis is investigated. This work explores the effect of chlorination temperature and ball-milling time on the microstructure, specific surface area (SSA) and the pore size distribution. It is found that the degree of order of CDC obtained from the milled titanium carbide (TiC) is obviously high and can be well tuned by controlling the ball-milling time at a lower chlorination temperature (400–800 °C). As the chlorination temperature rises to 1000 °C, an obvious decrease in the degree of order is observed and many cubic diamond-like carbon nanoparticles with larger d-spacing are formed. In addition, the produced CDC has a high SSA with both micro- and meso-pores. The effect of ball-milling TiC precursor on the microstructure of CDC can be attributed to the iron (Fe) in the TiC from the milling balls and jar to a great extent. The Fe promotes the formation of the better-organised carbon at lower chlorination temperature and the formation of the nano-diamond at higher temperature.     

Maximum power point tracking of partially shaded solar PV system using modified Fibonacci search method with fuzzy controller

This paper presents the modified Fibonacci search based Maximum Power Point Tracking (MPPT) scheme for a Solar Photovoltaic Array (SPVA) under partial shaded conditions. Partial shaded SPV modules produce several local maximum power points, which makes the tracking of the global maximum power a difficult task. Most of conventional tracking methods fail to work properly under these nonuniform insolation conditions. The real Fibonacci search based MPPT fails to track the global peak (GP) under partial shaded conditions. This paper improves the method by considering power ripple and wide search range so that the proposed method tracks GP for all the conditions. It is checked for different shading patterns through simulation and verified experimentally. In this paper, the advantage of using Fuzzy Logic Controller (FLC) is also presented. Fuzzy rules are optimized using genetic algorithm (GA). Comparative studies have been made for Proportional plus Integral (PI), nonoptimized FLC and GA optimized FLC. From the simulation results, it is observed that the fuzzy controller reduces error and it gives rapid response to environmental changes. Furthermore, it does not require any tuning of the parameters, unlike conventional PI controller, wherein the controller gain parameters needs to be changed when solar insolation changes.     

Analysis of transport phenomena within PEM fuel cells – An analytical solution

Transport phenomena within PEM fuel cells are investigated and a comprehensive analytical solution is presented. The methodology couples the transport within the fuel cell supply channels and the substrate which is composed of five different layers. The layers are all treated as macroscopically homogeneous porous media with uniform morphological properties such as porosity and permeability. The locally volume-averaged equations are employed to solve for transport through the porous layers. The problem encompasses complex interfacial transport phenomena involving several porous–porous as well as porous–fluid interfaces. Chemical reactions within the catalyst layers are also included. The method of matched asymptotic expansions is employed to solve for the flow field and species concentration distributions. Throughout the analysis, the choice of the gauge parameters involved in the perturbation solutions for velocity and concentration is found to be inherently tied to the physics of the problem and therefore an important physical metric. The analytical solution is found to be in excellent agreement with prior computational simulations. The analytical results are used to investigate several aspects of transport phenomena and their substantial role in PEM fuel cell operation. The solution presented in this work provides the first comprehensive analytical solution representing fuel cell transport phenomena.     

Microstructures and strength of microporous MgO-Mg(Al,Fe)2O4 refractory aggregates

Microporous MgO-Mg(Al, Fe)₂O₄ refractory aggregates were prepared using magnesite, Al(OH)₃ and Fe₂O₃ applying an in-situ decomposition synthesis method. At 1400–1600 °C, there was a Mg(Al, Fe)₂O₄ with Fe³⁺, which had two structures. One was a ring structure formed from Al(OH)₃ pseudomorph particle as a template and a low content of Fe³⁺. The other was the dot and strip structures precipitated in magnesite pseudomorph particles with a high content of Fe³⁺. Besides, at 1550–1600 °C, microporous MgO-Mg(Al, Fe)₂O₄ refractory aggregates had an excellent compressive strength (75.8–81.5 MPa) and apparent porosity (26.8%?28.2%).     

大数据驱动的动力电池健康状态估计方法综述

动力电池健康状态估计是电池管理系统关键算法之一,对提高动力电池能量利用效率、降低电池热失控风险,以及动力电池的维保和残值评估具有重要意义。对比分析试验法、模型法、数据驱动法的优势和不足,并以数据驱动方法为核心,分别从动力电池健康状态数据集构建、健康状态特征参数提取、健康状态估计模型三个方面对现阶段健康状态估计方法的理论基础和技术方案进行综述。总结常用的大数据采集方法以及数据预处理方法,明确大数据在健康状态评估中的意义。比较现有健康状态特征提取方法,对其优劣以及适用场景做了分析。阐述不同健康状态估计模型的基本原理,提出模型融合是未来技术发展方向。最后,面向未来大数据实车应用场景,对动力电池健康状态估计方面存在的问题和发展前景进行了总结和展望。     

基于鲁棒积分滑模的四轮轮毂电机驱动电动汽车电液复合制动防抱死控制研究

为了充分发挥四轮轮毂电机驱动电动汽车电机制动与液压摩擦制动响应快且独立可控的优势,提高紧急制动时车辆稳定性与安全性,提出一种基于鲁棒积分滑模的电液复合制动防抱死控制策略。采用分层控制架构,上层控制器为基于鲁棒积分滑模的车轮滑移率控制,下层控制器为电液复合制动力协调分配。建立整车动力学与电液复合制动系统模型,基于Simulink-AMESim-Carsim联合仿真平台,在四种典型制动工况下对上述电液复合制动防抱死控制策略进行仿真验证。结果表明,在无需实时获取路面附着系数与轮胎纵向力的情况下,所提出的控制策略仍能消除外界干扰使车轮滑移率收敛至期望值,适用于多种紧急制动工况,响应迅速且鲁棒性强;电机再生制动与液压摩擦制动可稳定协同工作,在保证制动可靠性的同时提升了乘坐舒适性。     

某电动汽车换挡机构驱动转矩对换挡品质的影响

以某电动汽车双离合器换挡执行机构的仿真模型为研究平台,研究了3种换挡控制策略下执行机构驱动转矩和换挡品质等参数.研究结果表明:执行机构换挡过程中,双离合器滑磨阶段,过大或者过小的驱动转矩会产生较差的换挡品质;双离合器的非滑磨阶段,较大的驱动转矩能够产生较好的换挡品质.