Biomass-derived Oxymethylene Ethers as Diesel Additives: A Thermodynamic Analysis

Conversion of biomass for production of liquid fuels can help in reducing the greenhouse gas (GHG) emissions which are predominantly generated by combustion of fossil fuels. Adding oxymethylene ethers (OMEs) in conventional diesel fuel has the potential to reduce soot formation during the combustion in a diesel engine. OMEs are downstream products of syngas, which can be generated by the gasification of biomass. In this research, a thermodynamic analysis has been conducted through development of data intensive process models of all the unit operations involved in production of OMEs from biomass. Based on the developed model, the key process parameters affecting the OMEs production including equivalence ratio, H2/CO ratio, and extra water flow rate were identified. This was followed by development of an optimal process design for high OMEs production. It was found that for a fluidized bed gasifier with heat capacity of 28 MW, the conditions for highest OMEs production are at an air amount of 317 tonne/day, at H2/CO ratio of 2.1, and without extra water injection. At this level, the total OMEs production is 55 tonne/day (13 tonne/day OME3 and 9 tonne/day OME4). This model would further be used in a techno-economic assessment study of the whole biomass conversion chain to determine the most attractive pathways.

Biomass-derived oxymethylene ethers as diesel additives: A techno-economic assessment

Conversion of agricultural biomass such as wood chips, wheat straw and forest residue for the production of fuels can help in reducing GHG emissions since they are considered as nearly carbon neutral. Around the world there is a significant amount of forest and agricultural-biomass available which could be used for the production of liquid fuels that can be blended with the petroleum-based diesel. Oxymethylene ethers (OMEs) can be derived from biomass via gasification, water-gas shift reaction and methanol production. The addition of OMEs to conventional diesel fuel has great potential to reduce soot formation during the combustion in diesel engines. Unlike methanol and dimethyl ether (DMM) which can also reduce soot formation, the physical properties of OMEs allow the use in modern diesel engines without significant change of the engines infrastructure. In this study, a detailed and data intensive process simulation model was developed to simulate all the unit operations involved in the production of OMEs from biomass. The unit operation considered include biomass drying, gasification, gas cleaning, water gas shift reaction, methanol production and OMEs synthesis. The simulation results were then utilized to conduct a detailed techno-economic assessment study of the whole biomass conversion chain to determine the most attractive pathways for OMEs production. Our recent study shows that the key parameters affecting the OMEs production are equivalence ratio, H2/CO ratio and optimal air flow. Overall, the cost of production ($/liter) of OMEs from different biomass feedstock in Alberta will be determined

Fault Diagnosis in Internal Combustion Engines Using Nonlinear Multivariate Statistics

This paper presents a statistical-based fault diagnosis scheme for application to internal combustion engines. The scheme relies on an identified model that describes the relationships between a set of recorded engine variables using principal component analysis (PCA). Since combustion cycles are complex in nature and produce nonlinear relationships between the recorded engine variables, the paper proposes the use of nonlinear PCA (NLPCA). The paper further justifies the use of NLPCA by comparing the model accuracy of the NLPCA model with that of a linear PCA model. A new nonlinear variable reconstruction algorithm and bivariate scatter plots are proposed for fault isolation, following the application of NLPCA. The proposed technique allows the diagnosis of different fault types under steady-state operating conditions. More precisely, nonlinear variable reconstruction can remove the fault signature from the recorded engine data, which allows the identification and isolation of the root cause of abnormal engine behaviour. The paper shows that this can lead to (i) an enhanced identification of potential root causes of abnormal events and (ii) the masking of faulty sensor readings. The effectiveness of the enhanced NLPCA based monitoring scheme is illustrated by its application to a sensor fault and a process fault. The sensor fault relates to a drift in the fuel flow reading, whilst the process fault relates to a partial blockage of the intercooler. These faults are introduced to a Volkswagen TDI 1.9 Litre diesel engine mounted on an experimental engine test bench facility.

Comparison of Experimental PIV Data and CFD Simulations for Flow in a Diesel Particulate Filter Inlet Diffuser

Flow maldistribution of the exhaust gas entering a Diesel Particulate Filter (DPF) can cause uneven soot distribution during loading and excessive temperature gradients during the regeneration phase. Minimising the magnitude of this maldistribution is therefore an important consideration in the design of the inlet pipe and diffuser, particularly in situations where packaging constraints dictate bends in the inlet pipe close to the filter, or a sharp diffuser angle. This paper describes the use of Particle Image Velocimetry (PIV) to validate a Computational Fluid Dynamic (CFD) model of the flow within the inlet diffuser of a DPF so that CFD can be used with confidence as a tool to minimise this flow maldistribution. PIV is used to study the flow of gas into a DPF over a range of steady state flow conditions. The distribution of flow approaching the front face of the substrate was of particular interest to this study. Optically clear diffusing cones were designed and placed between pipe and substrate to allow PIV analysis to take place. Stereoscopic PIV was used to eliminate any error produced by the optical aberrations caused by looking through the curved wall of the inlet cone. In parallel to the experiments, numerical analysis was carried out using a CFD program with an incorporated DPF model. Boundary conditions for the CFD simulations were taken from the experimental data, allowing an experimental validation of the numerical results. The CFD model incorporated a DPF model, the cement layers seen in segmented filters and the intumescent matting that is commonly used to pack the filter into a metal casing. The mesh contained approximately 580,000 cells and used the realizable ?-e turbulence model. The CFD simulation predicted both pressure drop across the DPF and the velocity field within the cone and at the DPF face with reasonable accuracy, providing confidence in the use the CFD in future work to design new, more efficient cones.

An optimized process design for oxymethylene ether production from woody-biomass-derived syngas

The conversion of biomass for the production of liquid fuels can help reduce the greenhouse gas (GHG) emissions that are predominantly generated by the combustion of fossil fuels. Oxymethylene ethers (OMEs) are a series of liquid fuel additives that can be obtained from syngas, which is produced from the gasification of biomass. The blending of OMEs in conventional diesel fuel can reduce soot formation during combustion in a diesel engine. In this research, a process for the production of OMEs from woody biomass has been simulated. The process consists of several unit operations including biomass gasifi- cation, syngas cleanup, methanol production, and conversion of methanol to OMEs. The methodology involved the development of process models, the identification of the key process parameters affecting OME production based on the process model, and the development of an optimal process design for high OME yields. It was found that up to 9.02 tonnes day1 of OME3, OME4, and OME5 (which are suitable as diesel additives) can be produced from 277.3 tonnes day1 of wet woody biomass. Furthermore, an optimal combination of the parameters, which was generated from the developed model, can greatly enhance OME production and thermodynamic efficiency. This model can further be used in a techno- economic assessment of the whole biomass conversion chain to produce OMEs. The results of this study can be helpful for petroleum-based fuel producers and policy makers in determining the most attractive pathways of converting bio-resources into liquid fuels.