Train speed trajectory optimization is a significant issue in railway traffic systems, and it plays a key role in determining energy consumption and travel time of trains. Due to the complexity of real-world operation...Train speed trajectory optimization is a significant issue in railway traffic systems, and it plays a key role in determining energy consumption and travel time of trains. Due to the complexity of real-world operational environments, a variety of factors can lead to the uncertainty in energy-consumption. To appropriately characterize the uncertainties and generate a robust speed trajectory, this study specifically proposes distance-speed networks over the inter-station and treats the uncertainty with respect to energy consumption as discrete samplebased random variables with correlation. The problem of interest is formulated as a stochastic constrained shortest path problem with travel time threshold constraints in which the expected total energy consumption is treated as the evaluation index. To generate an approximate optimal solution, a Lagrangian relaxation algorithm combined with dynamic programming algorithm is proposed to solve the optimal solutions. Numerical examples are implemented and analyzed to demonstrate the performance of proposed approaches.展开更多
With rapid development of the railway traffic, the moving block signaling system （MBS） method has become more and more important for increasing the track capacity by allowing trains to run in a shorter time-headway ...With rapid development of the railway traffic, the moving block signaling system （MBS） method has become more and more important for increasing the track capacity by allowing trains to run in a shorter time-headway while maintaining the required safety margins. In this framework, the tracking target point of the following train is moving forward with its leading train. This paper focuses on the energy saving tracking control of two successive trains in MBS. Nonlinear programming method is used to optimize the energy-saving speed trajectory of the following train. The real-time location of the leading train could be integrated into the optimization process. Due to simplicity, it can be used for online implementation. The feasibility and effectiveness are verified through simulation. The results show that the new method is efficient on energy saving even when disturbances present.展开更多
The development of battery electric(BE)heavy-duty trucks(HDTs)is highly limited to the short cycling life of batteries.In this paper,we propose a battery aging-conscious control strategy for extended battery life by o...The development of battery electric(BE)heavy-duty trucks(HDTs)is highly limited to the short cycling life of batteries.In this paper,we propose a battery aging-conscious control strategy for extended battery life by optimizing the speed trajectory of BE HDT.A state-space model is constructed by connecting the vehicle dynamics and battery state of charge,and a mechanism-based aging model of battery is then introduced to formulate the optimization problem for minimal battery aging and energy consumption.The optimization problem is solved within a model predictive control framework for the real-time speed control of the vehicle.A non-cooperative platooning controller is further developed for the vehicle in adaptation to the traffic,where the intervehicular distance is controlled for reducing the air drag coefficient so that both the energy consumption and battery aging are improved.Simulation results show that for the single-vehicle controller,the battery degradation and energy consumption are,respectively,reduced by up to 25.7%and 3.2%compared with the cruise control strategy.Based on the non-cooperative controller,the HDT is able to follow preceding vehicles with different parameters with battery aging and energy consumption further,respectively,reduced by 2%–5%and 9%–10%compared with those of the single-vehicle controller.展开更多
Electric trains typically travel across the railway networks in an inter-provincial,inter-city and intra-city manner.The electric train generally serves as a load/source in tractive/brake mode,through which power netw...Electric trains typically travel across the railway networks in an inter-provincial,inter-city and intra-city manner.The electric train generally serves as a load/source in tractive/brake mode,through which power networks and railway networks are closely coupled and mutually influenced.Based on the operational mode of rail trains and the characteristics of their load power,this paper proposes a coordinated optimal decisionmaking method of demand response for controllable load of rail trains and energy storage systems.First,a coordinated approach of dynamically adjusting the load of the controllable rail train in considering the driving comfort and energy storage battery is designed.Secondly,under the time conditions that satisfy the train’s operational diagram,the functional relationship between the train speed and the load power is presented.Based on this,in considering the constraints of the train’s arrival time,driving speed,motor power,and driving comfort,the capacity of energy storage batteries and other constraints,an optimization model for demand response in managing the traction power supply system under a two-part price and time-of-use(TOU)price is proposed.The objective is to minimize the energy consumption costs of rail transit trains,and optimize the speed trajectory of rail trains,the load power of traction system,and the output of energy storage batteries.展开更多
文摘Train speed trajectory optimization is a significant issue in railway traffic systems, and it plays a key role in determining energy consumption and travel time of trains. Due to the complexity of real-world operational environments, a variety of factors can lead to the uncertainty in energy-consumption. To appropriately characterize the uncertainties and generate a robust speed trajectory, this study specifically proposes distance-speed networks over the inter-station and treats the uncertainty with respect to energy consumption as discrete samplebased random variables with correlation. The problem of interest is formulated as a stochastic constrained shortest path problem with travel time threshold constraints in which the expected total energy consumption is treated as the evaluation index. To generate an approximate optimal solution, a Lagrangian relaxation algorithm combined with dynamic programming algorithm is proposed to solve the optimal solutions. Numerical examples are implemented and analyzed to demonstrate the performance of proposed approaches.
文摘With rapid development of the railway traffic, the moving block signaling system （MBS） method has become more and more important for increasing the track capacity by allowing trains to run in a shorter time-headway while maintaining the required safety margins. In this framework, the tracking target point of the following train is moving forward with its leading train. This paper focuses on the energy saving tracking control of two successive trains in MBS. Nonlinear programming method is used to optimize the energy-saving speed trajectory of the following train. The real-time location of the leading train could be integrated into the optimization process. Due to simplicity, it can be used for online implementation. The feasibility and effectiveness are verified through simulation. The results show that the new method is efficient on energy saving even when disturbances present.
基金funded by the Research Start-Up Funding of Chongqing University(Grant No.02090011044160)the National Natural Science Foundation of China(Grant No.51907136)。
文摘The development of battery electric(BE)heavy-duty trucks(HDTs)is highly limited to the short cycling life of batteries.In this paper,we propose a battery aging-conscious control strategy for extended battery life by optimizing the speed trajectory of BE HDT.A state-space model is constructed by connecting the vehicle dynamics and battery state of charge,and a mechanism-based aging model of battery is then introduced to formulate the optimization problem for minimal battery aging and energy consumption.The optimization problem is solved within a model predictive control framework for the real-time speed control of the vehicle.A non-cooperative platooning controller is further developed for the vehicle in adaptation to the traffic,where the intervehicular distance is controlled for reducing the air drag coefficient so that both the energy consumption and battery aging are improved.Simulation results show that for the single-vehicle controller,the battery degradation and energy consumption are,respectively,reduced by up to 25.7%and 3.2%compared with the cruise control strategy.Based on the non-cooperative controller,the HDT is able to follow preceding vehicles with different parameters with battery aging and energy consumption further,respectively,reduced by 2%–5%and 9%–10%compared with those of the single-vehicle controller.
基金This work was supported in part by the National Natural Science Foundation of China(71931003)the Science and Technology Projects of Hunan Province and Changsha City(2018GK4002,2019CT5001,2019WK2011,2019GK5015 and kq1907086).
文摘Electric trains typically travel across the railway networks in an inter-provincial,inter-city and intra-city manner.The electric train generally serves as a load/source in tractive/brake mode,through which power networks and railway networks are closely coupled and mutually influenced.Based on the operational mode of rail trains and the characteristics of their load power,this paper proposes a coordinated optimal decisionmaking method of demand response for controllable load of rail trains and energy storage systems.First,a coordinated approach of dynamically adjusting the load of the controllable rail train in considering the driving comfort and energy storage battery is designed.Secondly,under the time conditions that satisfy the train’s operational diagram,the functional relationship between the train speed and the load power is presented.Based on this,in considering the constraints of the train’s arrival time,driving speed,motor power,and driving comfort,the capacity of energy storage batteries and other constraints,an optimization model for demand response in managing the traction power supply system under a two-part price and time-of-use(TOU)price is proposed.The objective is to minimize the energy consumption costs of rail transit trains,and optimize the speed trajectory of rail trains,the load power of traction system,and the output of energy storage batteries.
