Estimation of the Diesel Particulate Filter Soot Load Based on an Equivalent Circuit Model

Du, Yiqun; Hu, Guangdi; Shun, Xiang; Zhang, Ke; Liu, Hongxing; Guo, Feng

doi:10.3390/en11020472

Cited by 14 publications

(9 citation statements)

References 27 publications

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“…Particulate matter or soot is created during the incomplete combustion of diesel fuel, which contributes to the problem by releasing particulates directly into the air and by emitting nitrogen oxides and sulfur oxides, which transform into secondary particulates in the atmosphere [1]. As emission regulations become more stringent, diesel engines must be equipped with after-treatment systems to meet emission requirements [1], [2], and according to U.S. Environmental Protection Agency (EPA ), diesel engine manufacturers are required to meet these regulations .…”

Section: Overviewmentioning

confidence: 99%

Soot Mass Estimation From Electrical Capacitance Tomography Imaging for a Diesel Particulate Filter

Hassan

Anwar

2019

Volume 4: Dynamics, Vibration, and Control

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The Electrical capacitance tomography (ECT) method has recently been adapted to obtain tomographic images of the cross section of a diesel particulate filter (DPF). However, a soot mass estimation algorithm is still needed to translate the ECT image pixel data to obtain soot load in the DPF. In this paper, we propose an estimation method to quantify the soot load in a DPF through an inverse algorithm that uses the ECT images commonly generated by a back-projection algorithm. The grayscale pixel data generated from ECT is used in a matrix equation to estimate the permittivity distribution of the cross section of the DPF. Since these permittivity data has direct correlation with the soot mass present inside the DPF, a permittivity to soot mass distribution relationship is established first. A numerical estimation algorithm is then developed to compute the soot mass accounting for the mass distribution across the cross-section of the DPF as well as the dimension of the DPF along the exhaust flow direction. Experimental data has been used to validate the proposed soot estimation algorithm which compared the estimated values with the actual measured soot mass. The estimated soot mass for various soot load amounts were found to correlate reasonably well with the measured soot masses in those cases.

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Section: Overviewmentioning

confidence: 99%

Soot Mass Estimation From Electrical Capacitance Tomography Imaging for a Diesel Particulate Filter

Hassan

Anwar

2019

Volume 4: Dynamics, Vibration, and Control

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“…Mohan et al [29] introduced an inventory model, considering delayed payments, budget constraints, and permissible partial payment (with penalty) for a multi-item production system with a replenishment policy. Todde et al [30] and Du et al [31] published the basic energy models, based on energy consumption and energy analysis. Cárdenas-Barrón et al [32] proposed an inventory model with an improved heuristic algorithm solving method for a just-in-time (JIT) system with the maximum available budget.…”

Section: Introductionmentioning

confidence: 99%

Multi-Product Production System with the Reduced Failure Rate and the Optimum Energy Consumption under Variable Demand

2019

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The advertising of any smart product is crucial in generating customer demand, along with reducing sale prices. Naturally, a decrease in price always increases the demand for any smart product. This study introduces a multi-product production process, taking into consideration the advertising- and price-dependent demands of products, where the failure rate of the production system is reduced under the optimum energy consumption. For long-run production systems, unusual energy consumption and machine failures occur frequently, which are reduced in this study. All costs related with the production system are included in the optimum energy costs. The unit production cost is dependent on the production rate of the machine and its failure rate. The aim of this study is to obtain the optimum profit with a reduced failure rate, under the optimum advertising costs and the optimum sale price. The total profit of the model becomes a complex, non-linear function, with respect to the decision variables. For this reason, the model is solved numerically by an iterative method. However, the global optimality is proved numerically, by using the Hessian matrix. The numerical results obtained show that for smart production, the maximum profit always occurs at the optimum values of the decision variables.

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“…Du et al [28] and Todde et al [29] developed the models considering energy consumption and energy analysis. In the Tomić and Schneider [30] model, the energy recovery methods were explained from the waste by applying a closed-loop energy recovery approach.…”

Section: Introductionmentioning

confidence: 99%

Effect of Electrical Energy on the Manufacturing Setup Cost Reduction, Transportation Discounts, and Process Quality Improvement in a Two-Echelon Supply Chain Management under a Service-Level Constraint

et al. 2019

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The need for efficient electrical energy consumption has greatly expanded in the process industries. In this paper, efforts are made to recognize the electrical energy consumption in a two-echelon supply chain model with a stochastic lead-time demand and imperfect production, while considering the distribution free approach. The initial investments are made for quality improvement and setup cost reduction, which ultimately reduce electrical energy consumption. The inspection costs are considered in order to ensure the good qualities of the product. Centralized and decentralized strategies are used to analyze the proposed supply chain model. The main objective of this study is to reduce the overall cost through efficient electrical energy consumption in supply chain management by optimizing the lot size, the number of shipments, the setup cost, and the failure rate. A quantity-based transportation discount policy is applied to reduce the expected annual costs, and a service-level constraint is incorporated for the buyer to avoid a stockout situation. The impact of the decision variables on the expected total costs is analyzed, and sensitivity analysis is carried out. The results show a significant reduction in overall cost, with quality improvement and setup cost reduction ultimately reducing electrical energy consumption.

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Estimation of the Diesel Particulate Filter Soot Load Based on an Equivalent Circuit Model

Cited by 14 publications

References 27 publications

Soot Mass Estimation From Electrical Capacitance Tomography Imaging for a Diesel Particulate Filter

Soot Mass Estimation From Electrical Capacitance Tomography Imaging for a Diesel Particulate Filter

Multi-Product Production System with the Reduced Failure Rate and the Optimum Energy Consumption under Variable Demand

Effect of Electrical Energy on the Manufacturing Setup Cost Reduction, Transportation Discounts, and Process Quality Improvement in a Two-Echelon Supply Chain Management under a Service-Level Constraint

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