Energy-Saving and Punctuality Combined Velocity Planning for the Autonomous-Rail Rapid Tram with Enhanced Pseudospectral Method

Autonomous-rail rapid transit(ART)is a new medium-capacity rapid transportation system with punctuality,comfort and convenience,but low-cost construction.Combined velocity planning is a critical approach to meet the requirements of energy-saving and punctuality.An ART velocity pre-planning and re-planning strategy based on the combination of punctuality dynamic programming(PDP)and pseudospectral(PS)method is proposed in this paper.Firstly,the longitudinal dynamics model of ART is established by a multi-particle model.Secondly,the PDP algorithm with global optimal characteristics is adopted as the pre-planning strategy.A model for determining the number of collocation points of the real-time PS method is proposed to improve the energy-saving effect while ensuring computation efficiency.Then the enhanced PS method is utilized to design the velocity re-planning strategy.Finally,simulations are conducted in the typical scenario with sloping roads,traffic lights,and intrusion of the pedestrian.The simulation results indicate that the ART with the proposed velocity trajectory optimization strategy can meet the punctuality requirement,and obtain better economy efficiency compared with the punctuality green light optimal speed advisory(PGLOSA).

Temperature Rise Calculation and Velocity Planning of Permanent Magnet Linear Synchronous Motor under Trapezoidal Speed

For permanent magnet linear synchronous motor(PMLSM) working at trapezoidal speed for long time, high thrust brings high temperature rise, while low thrust limits dynamic performance. Thus, it is crucial to find a balance between temperature rise and dynamic performance. In this paper, a velocity planning model of the PMLSM at trapezoidal speed based on electromagnetic-fluid-thermal(EFT) field is proposed to obtain the optimal dynamic performance under temperature limitation. In this model, the winding loss is calculated considering the acceleration and deceleration time. The loss model is indirectly verified by the temperature rise experiment of an annular winding sample. The actual working conditions of the PMLSM are simulated by dynamic grid technology to research the influence of acceleration and deceleration on fluid flow in the air gap, and the variation rule of the thermal boundary condition is analyzed. Combined with the above conditions, the temperature rise of a coreless PMLSM(CPMLSM) under the rated working condition is calculated and analyzed in detail. Through this method and several iterations, the optimal dynamic performance under the temperature limitation is achieved. The result is verified by a comparison between simulation and prototype tests, which can help improve the dynamic performance.

Energy-Optimal Braking Control Using a Double-Layer Scheme for Trajectory Planning and Tracking of Connected Electric Vehicles

Most researches focus on the regenerative braking system design in vehicle components control and braking torque distribution,few combine the connected vehicle technologies into braking velocity planning.If the braking intention is accessed by the vehicle-to-everything communication,the electric vehicles(EVs)could plan the braking velocity for recovering more vehicle kinetic energy.Therefore,this paper presents an energy-optimal braking strategy(EOBS)to improve the energy efficiency of EVs with the consideration of shared braking intention.First,a double-layer control scheme is formulated.In the upper-layer,an energy-optimal braking problem with accessed braking intention is formulated and solved by the distance-based dynamic programming algorithm,which could derive the energy-optimal braking trajectory.In the lower-layer,the nonlinear time-varying vehicle longitudinal dynamics is transformed to the linear time-varying system,then an efficient model predictive controller is designed and solved by quadratic programming algorithm to track the original energy-optimal braking trajectory while ensuring braking comfort and safety.Several simulations are conducted by jointing MATLAB and CarSim,the results demonstrated the proposed EOBS achieves prominent regeneration energy improvement than the regular constant deceleration braking strategy.Finally,the energy-optimal braking mechanism of EVs is investigated based on the analysis of braking deceleration,battery charging power,and motor efficiency,which could be a guide to real-time control.

Hierarchical predictive energy management strategy for fuel cell buses entering bus stops scenario

This paper aims to answer how to use traffic information to design energy management strategies for fuel cell buses in a networked environment.For the buses entering the bus stops scenario,this paper proposes a hierarchical energy management strategy for fuel cell buses,which considers the traffic information near the bus stops.In the upper-level trajectory planning stage,the optimal SOC trajectory under various historical traffic conditions is solved through dynamic planning.The traffic information and the best SOC trajectory are mapped through BiLSTM,which can achieve fast,real-time long-term SOC reference.In the lower-level real-time predictive energy management strategy,the optimal SOC is used as the state reference to guide the predictive energy management of fuel cell buses when entering the bus stops.Simulation results show that compared with the strategy without SOC trajectory reference,the life cost of the proposed strategy is reduced by 13.8%,and the total cost is reduced by 3.61%.The SOC of the proposed strategy is closer to the DP optimal solution.