Thermodynamic study of hydrogen production from crude glycerol autothermal reforming for fuel cell applications

This study presents a thermodynamic analysis of hydrogen production from an autothermal reforming of crude glycerol derived from a biodiesel production process. As a composition of crude glycerol depends on feedstock and processes used in biodiesel production, a mixture of glycerol and methanol, major components in crude glycerol, at different ratios was used to investigate its effect on the autothermal reforming process. Equilibrium compositions of reforming gas obtained were determined as a function of temperature, steam to crude glycerol ratio, and oxygen to crude glycerol ratio. The results showed that at isothermal condition, raising operating temperature increases hydrogen yield, whereas increasing steam to crude glycerol and oxygen to crude glycerol ratios causes a reduction of hydrogen concentration. However, high temperature operation also promotes CO formation which would hinder the performance of low-temperature fuel cells. The steam to crude glycerol ratio is a key factor to reduce the extent of CO but a dilution effect of steam should be considered if reforming gas is fed to fuel cells. An increase in the ratio of glycerol to methanol in crude glycerol can increase the amount of hydrogen produced. In addition, an optimal operating condition of glycerol autothermal reforming at a thermoneutral condition that no external heat to sustain the reformer operation is required, was investigated.     

Performance evaluation of combined solid oxide fuel cells with different electrolytes

The performance of a hybrid system of solid oxide fuel cells with different electrolytes, i.e., an oxygen-ion conducting electrolyte (SOFC-O²⁻) and a proton-conducting electrolyte (SOFC-H⁺) is evaluated in this study. Due to an internal reforming operation, SOFC-O²⁻ can produce electrical power as well as high-temperature exhaust gas containing remaining fuel, i.e., H₂ and CO that can be used for SOFC-H⁺ operation. The remaining CO can further react with H₂O via water gas-shift reaction to produce more H₂ within SOFC-H⁺ and thus, the possibility of carbon formation in SOFC-H⁺ can be eliminated and overall system efficiency can be improved. The simulation results show that the performance of the SOFC-O²⁻–SOFC-H⁺ system provides a higher efficiency (54.11%) compared with the use of a single SOFC. Further, the SOFC hybrid system performance is investigated with respect to important operating conditions, such as temperature, pressure, degree of pre-reforming, inlet fuel velocity, and cell voltage.     

Product quality improvement of batch crystallizers by a batch-to-batch optimization and nonlinear control approach

Batch crystallization is one of the widely used processes for separation and purification in many chemical industries. Dynamic optimization of such a process has recently shown the improvement of final product quality in term of a crystal size distribution (CSD) by determining an optimal operating policy. However, under the presence of unknown or uncertain model parameters, the desired product quality may not be achieved when the calculated optimal control profile is implemented. In this study, a batch-to-batch optimization strategy is proposed for the estimation of uncertain kinetic parameters in the batch crystallization process, choosing the seeded batch crystallizer of potassium sulfate as a case study. The information of the CSD obtained at the end of batch run is employed in such an optimization-based estimation. The updated kinetic parameters are used to modify an optimal operating temperature policy of a crystallizer for a subsequent operation. This optimal temperature policy is then employed as new reference for a temperature controller which is based on a generic model control algorithm to control the crystallizer in a new batch run.     

间歇结晶过程的分批优化

It is the fact that several process parameters are either unknown or uncertain. Therefore, an optimal control, profile calculated with developed process models with respect to such process parameters may not give an optimal performance when implemented to real processes. This study proposes a batch-to-batch optimization strategy for the estimation of uncertain kinetic.par.ameters in a batch crystallization process of potassium sulfate production. The knowledge of a crystal size distribution of the product at the end of batch operation is used in the proposed methodology. The updated kinetic parameters are applied for determining an optimal operating temperature policy for the next batch run.     

Optimization and nonlinear control of a batch crystallization process

Crystallization process has been widely used for separation in many chemical industries due to its capability to provide high purity product. To obtain the desired quality of crystal product, an optimal cooling control strategy is studied in the present work. Within the proposed control strategy, a dynamic optimization is first preformed with the objective to obtain the optimal cooling temperature policy of a batch crystallizer, maximizing the total volume of seeded crystals. Two different optimization problems are formulated and solved by using a sequential optimization approach. Owing to the complex and nonlinear behavior of the batch crystallizer, the nonlinear control strategy which is based on a generic model control (GMC) algorithm is implemented to track the resulting optimal temperature profile. The optimization integrated with nonlinear control strategy is demonstrated on a seeded batch crystallizer for the production of potassium sulfate.