Study On Models And Algorithms Of Train Operation Control Towards Energy Saving And Emission Reduction

With rapid development of the national economy, china’s railway transportation system has gained great achievements in construction and operation. However, as sustainability development is receiving more and more attention, railway system is confronted with multiple types of pressure concerned with other transportation’s competition and protecting environment against pollution. In the total energy consumption and exhausts emission of railway system, trains related energy consumption and exhausts emission have taken a large proportion and train operation system has a direct impact on rail business cost and the outer environment, so it is necessary to make studies on train operation control system from energy saving and emission reduction perspective. In this thesis, on the basis of sumarizing energy consumption and exhausts emission’s characteristics and laws, some optimization models of train operation for energy saving and emission reduction and their algorithms are stuided at two levels. One is from the level of train manipulation control, and the other is from the level of rail traffic management. While it is conducive to improve the rail transportation enterprise’s competitiveness by reducing energy consumption and cutting expenses, it’s also expected to help the enterprises fulfill their social obligations and put the sustainable transportation into effect.The main contributions and innovations in this thesis are as follows:1. According to one of energy-efficient mathematical models which usually use GA-based algorithm to solve using train control mode sequence, a new algorithm based on particle swarm optimization is applied to solve the model. Compared with other methods, it demonstrates these new PSO-based algorithms have a better performance in computation efficiency decreased by40%on the average without inferior results.2. On the basis of the power conservation principle and fuel use control model, a microscopic emission optimization model of train pulled by diesel locomotive is put forward using optimal control theory and a Lagrange-based method is employed to solve the model. By solving and comparing three simulation cases’ results, it’s found that minimizing traction mechanical energy doesn’t mean minimization of fuel consumption and exhausts emission and pointed out that the quantity ralationship between energy consumption and exhausts emission isn’t equivalent in theory.3. Using uncertain programming theory, an evaluation optimization model of diesel locomotive emission reduction technology used in marshalling railyard is proposed. Combined with random simulation, a bilevel hybrid intelligent algorithm is designed for the proposed model. Simulation case results demonstrate that expected operation cost for diesel locomotive using the correspongding emission reduction technology when its control efficiency is kept36.6%for PM and48.4%for NOx.4. Conidering the match between locomotives and lines, a multi-objective dynamic optimization model in freight transportation network is put forward and an augmented ε-constraint solving algorithm is designed. In the simulation case, the model and the algorithm will help to control the total energy consumption and exhausts emission in overall plan, and the efficiency for energy saving and emission reduction can be attained about by14%.5. On the basis of relevant train scheduling models for passenger train operation management, a multi-objective train scheduling model by assigning different locomotives to different trains with segment emission constraints is introduced and a fuzzy multi-objective optimization algorithm is employed to solve the model. A numerical example is performed and compared to illustrate the effectiveness of the proposed model for energy saving in different scenrios considering locomotive assignment and the energy efficiency can be got about by10%.6. Using time-space network formulation, a multi-objective optimization model of train energy consumption on a inter-city rail line is proposed on the basis of train time table predetermined. A simulation case is provided and solved for comparison and an optimization analysis is carried on via weighting method. The results demonstrate that energy saving can be attained by allocating rail stocks in stations reasonably and the energy efficiency is about by7%.