Ignition Pattern Analysis for Automotive Engine Trouble Diagnosis Using Wavelet Packet Transform and Support Vector Machines

Engine spark ignition is an important source for diagnosis of engine faults.Based on the waveform of the ignition pattern,a mechanic can guess what may be the potential malfunctioning parts of an engine with his/her experience and handbooks.However,this manual diagnostic method is imprecise because many spark ignition patterns are very similar.Therefore,a diagnosis needs many trials to identify the malfunctioning parts.Meanwhile the mechanic needs to disassemble and assemble the engine parts for verification.To tackle this problem,an intelligent diagnosis system was established based on ignition patterns.First,the captured patterns were normalized and compressed.Then wavelet packet transform（WPT） was employed to extract the representative features of the ignition patterns.Finally,a classification system was constructed by using multi-class support vector machines（SVM） and the extracted features.The classification system can intelligently classify the most likely engine fault so as to reduce the number of diagnosis trials.Experimental results show that SVM produces higher diagnosis accuracy than the traditional multilayer feedforward neural network.This is the first trial on the combination of WPT and SVM to analyze ignition patterns and diagnose automotive engines.

WEAR FAILURE MECHANISM AND MULTI-IMPACT PROPERTY OF AUTOMOTIVE ENGINE CHAIN

The multi-impact characteristics and failure mechanism of two kinds of automotive engine chain made in China are studied through engine assembly and road-drive tests. The worn surface morphologies of rubbing area between pin, bush and roller are also analyzed based on scanning electron microscope. The results show that the main wear mechanism of automotive engine chain is fatigue wear, and its failure mechanism is the forming, extending and flaking of cracks on top layer of pin and bush. In addition, the material, hot-treatment method and shaping technique for roller have a great influence upon the resistance to multi-impact. Ensuring sufficient strength and plasticity of roller, as well as adopting suitable shaping technique are the effective method to increase its resistance to multi-impact.

EXPERIMENTAL STUDY ON HIGH-SPEED CHARACTERISTICS OF AUTOMOTIVE ENGINE OIL-PUMP CHAIN

The high-speed multi-cycle impact and speed, load fluctuant characteristics of a kind of narrow-width automotive engine oil-pump chain 06BN-1 are studied through engine assembly and road-drive tests to satisfy the light-weight demand of engine. The worn surface morphologies of rubbing area between pin, bush and roller are also analyzed based on scanning electron microscope. The results show that the main wear mechanism of automotive engine oil-pump chain is fatigue wear, and it＇s failure mechanism is the forming, extending and flaking of cracks on top layer of pin and bush. Pin and bush both occurred cycle-soften phenomenon, and roller occurred cycle-harden. Fretting wear is one of the most important ＂fall to pieces＂ failure causes of automotive chain. Ensuring sufficient strength and plasticity of roller, as well as adopting suitable shaping technology are the effective methods to increase its resistance to multi-cycle impact.

Modelling of modern automotive petrol engine performance using Support Vector Machines

Modern automotive petrol engine performance is significantly affected by effective tune-up. Current practice of engine tune-up relies on the experience of the automotive engineer, and tune-up is usually done by trial-and-error method and then the vehicle engine is run on the dynamometer to show the actual engine performance. Obviously the current practice involves a large amount of time and money, and then may even fail to tune up the engine optimally because a formal performance model of the engine has not been determined yet. With an emerging technique, Support Vector Machines (SVM), the approximate per- formance model of a petrol vehicle engine can be determined by training the sample engine performance data acquired from the dynamometer. The number of dynamometer tests for an engine tune-up can therefore be reduced because the estimated engine performance model can replace the dynamometer tests to a certain extent. In this paper, the construction, validation and accuracy of the model are discussed. The study showed that the predicted results agree well with the actual test results. To illustrate the significance of the SVM methodology, the results were also compared with that regressed using multilayer feedforward neural networks.

Numerical Study on Application of CuO-Water Nanofluid in Automotive Diesel Engine Radiator

Application of CuO-water nanofluid with size of the nanoparticles of 20 nm and volume concentrations up 2% is numerically investigated in a radiator of Chevrolet Suburban diesel engine under turbulent flow conditions. The heat transfer relations between airflow and nanofluid coolant have been obtained to evaluate local convective and overall heat transfer coefficients and also pumping power for nanofluid flowing in the radiator with a given heat exchange capacity. In the present study, the effects of the automotive speed and Reynolds number of the nanofluid in the different volume concentrations on the radiator performance are also investigated. The results show that for CuO-water nanofluid at 2% volume concentration circulating through the flat tubes with Renf = 6000 while the automotive speed is 70 km/hr, the overall heat transfer coefficient and pumping power are approximately 10% and 23.8% more than that of base fluid for given conditions, respectively.

Exhaust gas energy recovery system of pneumatic driving automotive engine

Almost the same quantity to net output work of energy has been carried out and wasted by exhaust gas in typical automotive engine. Recovering the energy from exhaust gas and converting to mechanical energy will dramatically increase the heat efficiency and decrease the fuel consumption. With the increasing demand of fuel conservation, exhaust gas energy recovery technologies have been a hot topic. At present, many researches have been focused on heating or cooling the cab, mechanical energy using and thermo-electronic converting. Unfortunately, the complicated transmission of mechanical energy using and the depressed efficiency of thermo-electronic converting restrict their widely applying. In this paper, a kind of exhaust gas energy recovery system of pneumatic driving automotive engine, in which highly compressed air acts as energy storing and converting carrier, has been established. Pneumatic driving motor can produce moderate speed and high torque output, which is compatible for engine using. The feasibility has been certificated by GT-Power simulation and laboratory testes. The technologies about increasing recovery efficiency have been discussed in detail. The results demonstrated that the in parallel exhaust gas energy recovery system, which is similar to the compound turbo-charger structure can recovery 8 to 10 percent of rated power output. At last, a comprehensive system, which includes Rankine cycle based power wheel cycle unit etc., has been introduced.

Engineering Intelligent Racing Concepts Using Design Research Methods

The automotive seat market is positioned to significantly grow over the next five years. Research into how sensor implementation in every day driver cars can enhance driver wellness is becoming increasingly popular and visible in the automotive seat industry. However, in the competitive race car industry,?drivers prioritize driving ability over wellness. To further examine this phenomenon, the Human-Machine Interaction?Lab at the Georgia Institute of Technology took a unique approach to developing strong use cases for implementing sensor technology to improve driving ability for race car drivers by combining qualitative and quantitative research data obtained through modern design research and planning methodology. Following a process relying heavily on user-centered design methods, the authors developed a business case concept?for?a sensor-based seat accessory that acts as a competitive racer’s?driving coach?that is able to identify the mechanics of braking, turning, and accelerating through pressure sensors in the driver’s seat pan surface. This technology allows drivers to precisely understand when and how hard to brake, turn, or accelerate out of turns, thus reducing heat times and financial burden for drivers.

Adaptive Back-Stepping Control of Automotive Electronic Control Throttle

Back-stepping control (BSC), which is deemed effective for a non-holonomic system, is applied to improving both responsiveness and resolution performance of an electronic control throttle (ECT) used in automotive engines. This paper is characterized by the use of a two-step type BSC in a manner that achieves an improvement in responsiveness with the ETC operated in a fully opened state by adding a derivative term in Step 1 and the improvement in resolution performance with the ETC operated in a minutely opened state by adding an adaptive feature in the form of an integral term using the control deviation in Step 2. This paper presents an ECT control expressed as a second-order system including nonlinearities such as backlash of gear train and static friction in sliding area, a BSC system designed based on Lyapunov stability, and a determination method for control parameters. Also, a two-step type BSC system is formulated using Matlab/Simulink with a physics model as a control object. As a result of simulation analyses, it becomes clear that the BSC system can achieve quicker response because the derivative term works effectively and finer resolution because the adaptive control absorbs the error margin of the nonlinear compensation than conventional PID control.

Investigation into precision engineering design and development of the next-generation brake discs using Al/SiC metal matrix composites

Substantially lightweight brake discs with high wear resistance are highly desirable in the automotive industry.This paper presents an investigation of the precision-engineering design and development of automotive brake discs using nonhomogeneous Al/SiC metal-matrixcomposite materials.The design and development are based on modeling and analysis following stringent precision-engineering principles,i.e.,brake-disc systems that operate repeatably and stably over time as enabled by precision-engineering design.The design and development are further supported by tribological experimental testing and finite-element simulations.The results show the industrial feasibility of the innovative design approach and the application merits of using advanced metal-matrix-composite materials for next-generation automotive and electric vehicles.

Conceptual design of automobile engine rubber mounting composite using TRIZ-Morphological chart-analytic network process technique

An engine rubber mounting is one of the important parts of a vehicle. It is a function to isolate or absorb and to reduce vibration to the vehicle body thus to the passenger itself. Due to the engine compartments environment such as heat and massive vibration due to road conditions, the engine rubber mountings lifespan has been reduced. Thus several studies have been conducted to upgrade the material lifespan to make it more reliable and better engine mounting components. This paper presents the conceptual design of kenaf fiber polymer as automotive engine rubber mounting composites using the integration of Theory of Inventive Problem Solving(TRIZ). In this early stage, the solution is generated using 40 inventive principles and TRIZ contradiction method. The solution parameter for the specific design character is the selected using the morphological chart to develop a systematic conceptual design for the component. Four(4) innovative design concepts were produced and Analytic Network Process(ANP)methods were utilized to perform the multi-criteria decision-making process of selecting the best concept design for the polymer composite engine rubber mounting component.

Identification of Axial Vibration Excitation Source in Vehicle Engine Crankshafts Using an Auto-regressive and Moving Average Model

Violent axial vibration of a vehicle engine crankshaft might lead to multiple defects to the engine.Much research on mechanism and control measures has been done on engines,such as using the dynamic stiffness matrix method,rayleigh differential method,and system matrix method.But the source of axial vibration has not been identified clearly because there are many excitation factors for the axial vibration of a crankshaft,such as coupled torsional-axial vibration and coupled bending-axial vibration,etc.In order to improve the calculation reliability and identify the excitation source of axial vibration of in vehicle engine crankshafts,this paper presents a method to identify the axial vibration excitation source of crankshafts for high speed diesel engines based on an auto-regressive and moving average（ARMA） model.Through determining initial moving average variables and measuring axial /bending/torsional vibrations of a crankshaft at the free-end of a 4-cylinder diesel engine,autoregressive spectrum analysis is applied to the measured vibration signal.The results show that the axial vibration of the crankshaft is mainly excited by coupled bending vibration at high speed.But at low speed,the axial vibration in some frequencies is excited primarily by torsional excitation.Through investigation of axial vibration source of engine crankshafts,calculation accuracy of vibration can be improved significantly.

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.

Optimization of Transducer Location for Novel Non-Intrusive Methodologies of Diagnosis in Diesel Engines

The health monitoring has been studied to ensure integrity of design of engine structure by detection,quantification,and prediction of damages.Early detection of faults may allow the downtime of maintenance to be rescheduled,thus preventing sudden shutdown of machines.In cylinder pressure developed,vibrations and noise emissions data provide a rich source of information about condition of engines.Monitoring of vibrations and noise emissions are novel non-intrusive methodologies for which positioning of various transducers are important issue.The presented work shows applicability of these diagnosis methodologies adopted in case of diesel engines.The effects of changing various fuel injection parameters was analyzed.Scope of using non-intrusive technique has been analyzed by changing locations of microphone.Novelty of this worklies in exploring signal processing methods for various locations around the engine test set up.Various frequency ranges of contributing noise and vibration sources were identified.Time-Frequency analysis showed the onset of various cyclic.Based on the identification of various frequency bands,it is possible to device suitable filters in order to extract more information.

基于应力等效关系的汽车零部件疲劳寿命预测模型

对于预测多级应力加载下的汽车零部件疲劳寿命,已有的相关非线性模型通常需要依赖大量的试验数据,或者较难选取合适的基准值,使得疲劳可靠性理论在汽车领域的应用存在一定局限性。针对此问题,基于材料疲劳寿命特性曲线,通过分析两级应力之间疲劳损伤转化过程,建立了一种考虑相邻载荷作用的等效转化关系,推导了两级、三级及更高应力等级情况下相邻应力之间的疲劳累积损伤等效公式和剩余疲劳寿命的表达式,进而提出了一种基于应力等效关系的疲劳寿命预测模型。该模型的计算过程仅需不低于两级应力的材料疲劳寿命试验结果。采用二级、三级、四级及五级应力加载试验数据,分别计算并对比了Miner模型、Manson模型、Subramanyan模型、Hashin模型及新模型的相对误差平均值和最大值,进一步汇总了两级至五级应力下各模型疲劳累积损伤与疲劳累积寿命的预测结果、各模型预测疲劳损伤与试验疲劳损伤之差的分布。结果表明,基于相邻载荷作用等效转化的新模型在疲劳寿命的整体预测结果优于Miner模型、Manson模型、Subramanyan模型及Hashin模型,可更为准确地应用于材料多级应力下的疲劳寿命/损伤预测。

概率融合的抗侧翻智能主动悬架控制研究

为了提升高质心车辆的侧倾稳定性和平顺性,降低车辆侧翻事故造成的伤亡率,提出一种基于概率融合隶属度函数构建理论的侧翻工况预测和控制方法。首先,通过采集车辆侧翻工况数据,选取车辆状态变量,基于影响权重确定与车辆侧翻相关的关键影响因子。其次,根据时间序列对数据进行时间片段划分,设计动态贝叶斯预测网络,对下一时间片段内车辆侧翻概率进行预测。最后,根据车辆性能参数与控制器参数的映射规则,建立概率融合的Takagi-Sugeno(T-S)模糊隶属度函数,设计车辆主动悬架抗侧翻鲁棒控制器。CARSIM/Simulink联合仿真结果表明,与被动悬架、半主动悬架、多目标控制主动悬架相比,所提方法可以平稳且高效地防止车辆侧翻,提升车辆行驶的安全性。

中国混合动力汽车动力总成技术进展

在国家政策与市场需求的双重驱动下,2021年以来,中国品牌混合动力汽车动力总成技术实现突破,围绕中国市场特点与消费者用车习惯推出一批具有中国特色、世界范围内领先的混合动力汽车产品。近期混合动力汽车市场销量呈爆发式增长,2023年中国市场混合动力乘用车销售超300万辆,同比增长83%。然而,受近年来汽车领域电动化浪潮影响,行业内尚存关于混合动力汽车仅为过渡性技术的观点,部分消费者对国产混动汽车技术产品力仍存质疑。为纠正对混合动力汽车的片面性、偏见性认识,该文围绕中国混合动力汽车动力总成技术路线展开,聚焦多样化的混动架构与专用化的核心部件,提出新的混合度定义作为动力总成电气化程度的统一评价标准,探讨国内外主流混动技术异同,剖析当下中国最前沿的混动技术特点与发展趋势,厘清中国混动汽车动力总成的发展脉络。研究表明:中国式混动汽车以大容量动力电池与插电式混合动力为技术特色,实现发动机、电机两大驱动动力源以及动力电池、增程系统两大动力能量源的灵活混合与优势互补。与纯内燃机车相比,得益于电驱动技术辅助,混合动力汽车聚焦提高发动机热效率、发动机高效区利用率以及整车燃油经济性。与纯电动车相比,混合动力汽车则基于发动机的增程发电,以高性价比和高便利度解决纯电动车的补能焦虑;并通过结合发动机直驱、变速器动力放大等机械驱动技术,以更低的硬件成本实现更稳定的强劲动力输出。混合动力汽车的独特优势使其作为长期性技术路线,将成为带动汽车产业向碳中和方向转型升级的关键,该文对当下市场的深度分析和未来趋势的理性推测将为中国混动技术的进一步发展提供有益参考。

智能汽车轨迹跟踪多目标显式模型预测控制

针对现有智能汽车轨迹跟踪控制算法难以同时保证跟踪精确性、横向稳定性、舒适性以及控制实时性的问题,提出了一种基于多目标优化和显式模型预测控制理论的轨迹跟踪控制策略(MO-EMPC)。首先,建立考虑跟踪精确性、横向稳定性、舒适性的多目标函数及约束。然后,针对传统MPC控制实时性低的问题,设计基于EMPC的多目标优化轨迹跟踪控制器,通过引入多参数二次规划(MPQP)理论,将反复在线优化求解过程转化为等价的分段仿射系统(PPWA),离线计算得到最优显式控制律以供实时控制调用,减少在线运算时间。最后,基于CarSim/Simlink联合仿真方法,将所设计控制器的轨迹跟踪多目标优化效果与MPC控制效果进行对比验证。研究结果表明,所提出的轨迹跟踪策略在保证良好的跟踪精度前提下,横向稳定性、舒适性方面的表现更优于MPC控制器,且算法在线运行速度提高56.63%。

汽车发动机的能效与环保性能研究

随着城市化进程的不断加快,越来越多的人选择汽车出行,汽车的生产和应用为人们的生活提供了极大的便利,但是由汽车尾气等所导致的环境污染问题也越来越严重。发动机作为汽车的核心部件,其决定着汽车的能效,同时其设计工作也关乎汽车环保性,因此汽车发动机能效与环保性兼具成为当前研究的重点,本文将一次为基础,对汽车发动机节能原理进行分析,提出汽车发动机保持能效和提升环保性的措施,以及未来发展趋势,旨在为相关人员提供参考借鉴价值。

基于Manson-Halford模型改进的疲劳损伤预测模型

为了预测在多级应力加载条件下汽车零部件的疲劳损伤,提出一种基于Manson-Halford模型改进的疲劳损伤预测模型。首先,基于材料S-N特性曲线的关系式,在解析Gao模型中非线性作用系数的结构形式及构成要素的基础上,分析并引入相邻应力幅值之比、材料S-N对数特性直线的斜率、前一级疲劳累积损伤这3项参数,作为非线性疲劳损伤模型中作用系数的构成要素。在兼顾Manson-Halford模型原有优势的基础上,提出基于Manson-Halford模型改进的疲劳损伤预测模型。其次,为验证新模型的预测效果,采用了4种材料的两级至五级疲劳试验数据,从疲劳损伤绝对误差的最大值与疲劳损伤相对误差的最大值两项指标,分别对比了Miner模型、Manson-Halford模型、Gao模型、YG模型、Yue模型、Haghgouei模型及新模型的预测结果。其中,疲劳试验数据不仅涉及高周寿命的情况,也包含高周寿命与低周寿命相结合的情况。最后,对两级至五级疲劳损伤预测结果与试验结果之差进行了统计分析,利用最小值、最大值及标准差统计值判定各模型的优劣性。结果表明:提出的新模型与试验结果吻合,特别在低周疲劳与高周疲劳混合应力时,新模型的预测效果相较于其他几种模型具有一定优势,证明了新模型在疲劳损伤预测方面具有较高的精确性和鲁棒性。

吸能盒式前防撞横梁系统的碰撞吸能特性研究

前防撞横梁系统是提高整车安全性的重要部件,其中,吸能盒和横梁的结构参数直接影响车体的耐撞性能。为得到吸能盒式前防撞横梁系统的优化方案,首先,从压溃形式、初始峰值力和比吸能3个角度,研究了吸能盒截面结构对耐撞性能影响;然后,从抗弯强度和吸能值两个维度,研究了横梁截面结构对耐撞性能的影响;最后,研究了正碰和偏碰情形下,优化后吸能盒式前防撞横梁系统的耐撞性能。研究结果表明,正六边形截面具有较好的吸能效果;“目”字形截面横梁抗弯强度高且吸能效果好;新型吸能盒式前防撞横梁系统相较于传统系统而言,在正碰和偏碰情形下,吸能值分别提高了11.5%和31.6%,侵入量分别降低了53.2%和38.4%。这为优化防撞梁系统安全性能的研究提供了支持。