Abstract:Energy storage systems (ESS) play an important role in the performance of mining vehicles. A hybrid ESS combining both batteries (BTs) and supercapacitors (SCs) is one of the most promising solutions. As a case study, this paper discusses the optimal hybrid ESS sizing and energy management strategy (EMS) of 14-ton underground load-haul-dump vehicles (LHDs). Three novel contributions are added to the relevant literature. First, a multi-objective optimization is formulated regarding energy consumption and the total cost of a hybrid ESS, which are the key factors of LHDs, and a battery capacity degradation model is used. During the process, dynamic programming (DP)-based EMS is employed to obtain the optimal energy consumption and hybrid ESS power profiles. Second, a 10-year life cycle cost model of a hybrid ESS for LHDs is established to calculate the total cost, including capital cost, operating cost, and replacement cost. According to the optimization results, three solutions chosen from the Pareto front are compared comprehensively, and the optimal one is selected. Finally, the optimal and battery-only options are compared quantitatively using the same objectives, and the hybrid ESS is found to be a more economical and efficient option.
The pantograph catenary system plays an important role in the power performance of electric mining vehicles. A pantograph catenary system combining both a pantograph and a catenary is one of the most promising solutions. As a case study, this paper discusses the dynamic performance and the stable current collection of a pantograph catenary system for a 14 ton underground overhead wire electrical actuated load, haul, dump machine (LHD). First, based on the optimized finite element simulation process, finite element models of the pantograph system and the catenary system are established. Second, the motion equation of the catenary is improved, and the finite element model of the pantograph catenary system is established. Finally, a dynamic simulation experiment is performed to determine the dynamic performance of the pantograph catenary system. The results show that when the radius of the contact wire is set to 0.00564 m and the tension of contact wire is set to 30 KN, the current collection indexes of the pantograph catenary system meet the requirements of stable current collection and are superior to the simulation results of related references. Therefore, the validity of the finite element model is verified; thus, the pantograph catenary system can stably charge and supply energy for the trolley wire overhead electrically actuated LHD and ensure sufficient power.
In this paper, identification of an appropriate hybrid energy storage system (HESS) architecture, introduction of a comprehensive and accurate HESS model, as well as HESS design optimization using a nested, dual-level optimization formulation and suitable optimization algorithms for both levels of searches have been presented. At the bottom level, design optimization focuses on the minimization of power loss in batteries, converter, and ultracapacitors (UCs), as well as the impact of battery depth of discharge (DOD) to its operation life, using a dynamic programming (DP)-based optimal energy management strategy (EMS). At the top level, HESS optimization of component size and battery DOD is carried out to achieve the minimum life-cycle cost (LCC) of the HESS for given power profiles and performance requirements as an outer loop. The complex and challenging optimization problem is solved using an advanced Multi-Start Space Reduction (MSSR) search method developed for computation-intensive, black-box global optimization problems. An example of load-haul-dump (LHD) vehicles is employed to verify the proposed HESS design optimization method and MSSR leads to superior optimization results and dramatically reduces computation time. This research forms the foundation for the design optimization of HESS, hybridization of vehicles with dynamic on-off power loads, and applications of the advanced global optimization method.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.