Analysis and optimisation of emissions and fuel economy of biodiesel fuelled CI engine using Taguchi technique
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The objectives of the present work are to examine the combined effect of engine operating and injection parameters and to optimise these parameters for better fuel economy, performance, and reduced emissions. The fuels used were diesel and biodiesel blends of Jatropha and Karanja biodiesel. The results indicate that diesel gives higher thermal efficiency at low loads, however, the 20% jatropha blend was slightly more efficient, at high loads. It was observed that the BSFC increases when the EGR is varied from 0% to 20%. Even though the smoke opacity increases with increased EGR, advanced injection at 28o BTDC decreases smoke. Increased EGR also reduced NOx emissions by up to 11%. Blending also has a significant impact on the output parameters. Taguchi analysis was applied to optimise the performance and emission characteristics of the diesel engine and set of input values were obtained for the optimum performance under different conditions.In the manufacturing industry, to produce the best quality product, it is important to define several levels of inputs. The Taguchi method is proposed for the solution of this problem and is widely used. In this study, a steady-state genetic algorithm (GA), called Genmak, is developed for the solution of the experimental design problems. In order to compare the performance of the suggested algorithm with that of the Taguchi method, 3 sets with different characteristics are carefully designed. Each set has 1000 test problems. Each of these test problems is an experimental design problem having 4 factors with 3 levels. Significant effects and optimum solution are determinated by statistical methods for every problem generated. Two methods are applied to the problems and the number of problems in which the optimum solution is reached is recorded. Then, the methods are compared with respect to these records. The results show that the performance of the GA is as high as that of the Taguchi method. Another important result is that the performance of the methods decreases as the amount of interaction in a problem increases. Overall, it is concluded that GAs are suitable for finding the optimum solution to this kind of problem and can be used as an alternative to the Taguchi method.
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As one of the most fuel-efficient diesel locomotives in the world,HXN3diesel locomotive can track more wagons with less fuel and lower emission.But the substantial noise and of HXN3locomotive cab will provide less crew comfort,more equipment and manufacturing cost.The paper will analysis the vibration of the cab,and optimize the vibration isolation system.
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Taguchi method is a technique widely used in industries to attain a reliable quality even under existence of various noise variables. Basically, it relies on the interactions between the controllable and the noise factors. Under insignificant interactions between the design parameters and noises, the effectiveness of Taguchi methodology will be doubtful. Furthermore, existence of strong interactions among controllable factors may undermine the power of Taguchi approach. An abundant crop may be expected by a well planned Taguchi approach. A well designed set of experiments is one of the important prerequisites for its successful result. For this, we must have a clear understanding on strengths and weaknesses of Taguchi methodology together with a sound knowledge on the applicable system. This study provides some insights on Taguchi approach based on two case examples of one successful and the other unsuccessful. Eventually, this research aims to facilitate deeper understanding and right application of Taguchi methodology in industries.
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This paper presents the implementation of the Taguchi method for a retrofit design of a line-start permanent magnet motor. To evaluate the viability of the method, the optimum designs obtained from both the Taguchi and a traditional optimization methods are compared. This outlines the respective advantages and disadvantages of both methods. It shows that the Taguchi method is an efficient and robust design approach and possesses some unique advantages compared to conventional design methods. A design sensitivity investigation regarding the variances of certain parameters, due to manufacturing tolerances and material properties discrepancies, is also presented using the Taguchi method. From this investigation insight into the contribution of each parameter towards machine performance is gained for the steady-state performance of an embedded radial flux line-start permanent magnet motor.
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In this paper, the bursting strength of knitted fabrics was optimised using the Taguchi experiment design technique, which is a recently famous approach. In the evaluations, analyses of variance (ANOVA) and the signal to noise ratio were used. 9 experiments were performed with respect to the L9 orthogonal design for the Taguchi approach. The results show a considerable improvement in the S/N ratio as compared to the initial condition. With the Taguchi processes, we can easily determine optimum conditions for maximising the bursting strength of knitted fabrics with simple experiments.
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Biodiesel 燃料被发现基于研究人员出版一十年的结果是为石油柴油机的一种有希望的选择。Biodiesel 燃料是可更新、非可能减解的燃料。许多国家使用 biodiesel 燃料让 automotives 由于石油燃料的弄空遇见危机并且遇见紧排放标准。当来源和可估计的结果被报导，各种各样的研究与蔬菜油与不同 biodiesel 燃料被执行了。已经被测试了的很少 biodiesel 燃料是 Jatropha， Pongamia， Mahua， neem，棉花种子，等等。在这个试验性的工作， Adelfa biodiesel 混合被用作测试燃料。排放和表演特征与三另外的不同 biodiesel 燃料混合相比。可估计的结果暗示 Adelfa biodiesel (Nerium 油甲基酉旨) 能是未来的 biodiesel 燃料，它与直接注射(DI ) 有好相容性没有任何主要修正的柴油机引擎。而且， Adelfa 能与水的更少来源一起在一块非农业的陆地被栽培。它广泛地在亚洲的所有主要国家上被散布。试验性的调查与标准引擎说明在一台单个柱体 DI 柴油机引擎上被执行了。在这个试验性的工作，各种各样的 Adelfa biodiesel 相配与引用燃料(柴油机) 相比选择把更靠近的表演给柴油机的最好的混合。有另外的 biodiesel 燃料的比较分析也被做了，结果被讨论了。
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Taguchi defined a good quality as ‘A correspondence of product characteristic’s expected value to the objective value satisfying the minimum variance condition.’ For his good quality, he suggested Taguchi Method which is called Robust design which is irrelevant to the effect of these noise factors. Taguchi Method which has many success examples and which is used by many manufacturing industry. But Opti-mal solution of Taguchi Method is one among the experiments which is not optimal area of experiment point.On the other hand, Response Surface Method (RSM) which has advantage to find optimal solution area experiments points by approximate polynomial regression. But Optimal of RSM is depended on initial point and RSM can not use many factors because of a great many experiment. In this paper, we combine the Taguchi Method and the Response Surface Method with each advantage which is called Taguchi-RSM. Taguchi-RSM has two step, first step to find first solution by Taguchi Method, second step to find optimal solution by RSM with initial point as first step solution. We give example using catapults.
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Abstract The methods of Taguchi have received considerable attention in recent years. Part of the attention is due to the success of Genichi Taguchi and his colleagues and part of the attention is due to the mystique and controversy surrounding these methods. In this paper we discuss two separate aspects of the Taguchi method: the strategy of Taguchi and the tactics of Taguchi. The Taguchi tactics involve the specific methods and techniques recommended by Taguchi such as the use of signal-to-noise ratios and the so-called Taguchi designs. We discuss the parameter design strategy of Taguchi for designing and improving products and processes from a statistical point of view. We point out that although there are some apparent flaws in Taguchi's tactics, the basic strategy is a sound one.
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Taguchi parameter design is an approach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used signal-to-noise(SN) ratio to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. Many statisticians criticize the Taguchi techniques of analysis, particularly those based on SN ratio. In this paper we propose a substantially simpler optimization procedure for parameter design without resorting to SN ratio.
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