A complete road-soft ground model is established in this paper to study the dynamic responses caused by vehicle loads and/or daily temperature variation.A dynamic thermo-elastic model is applied to capturing the behav...A complete road-soft ground model is established in this paper to study the dynamic responses caused by vehicle loads and/or daily temperature variation.A dynamic thermo-elastic model is applied to capturing the behavior of the rigid pavement,the base course,and the subgrade,while the soft ground is characterized using a dynamic thermo-poroelastic model.Solutions to the road-soft ground system are derived in the Laplace-Hankel transform domain.The time domain solutions are obtained using an integration approach.The temperature,thermal stress,pore water pressure,and displacement responses caused by the vehicle load and the daily temperature variation are presented.Results show that obvious temperature change mainly exists within 0.3 m of the road when subjected to the daily temperature variation,whereas the stress responses can still be found in deeper places because of the thermal swelling/shrinkage deformation within the upper road structures.Moreover,it is important to consider the coupling effects of the vehicle load and the daily temperature variation when calculating the dynamic responses inside the road-soft ground system.展开更多
ELD （economic load dispatch） problem is one of the essential issues in power system operation. The objective of solving ELD problem is to allocate the generation output of the committed generating units. The main co...ELD （economic load dispatch） problem is one of the essential issues in power system operation. The objective of solving ELD problem is to allocate the generation output of the committed generating units. The main contribution of this work is to solve the ELD problem concerned with daily load pattern. The proposed solution technique, developed based PSO （particle swarm optimization） algorithm, is applied to search for the optimal schedule of all generations units that can supply the required load demand at minimum fuel cost while satisfying all unit and system operational constraints. The performance of the developed methodology is demonstrated by case studies in test system of six-generation units. The results obtained from the PSO are compared to those achieved from other approaches, such as QP （quadratic programming）, and GA （genetic algorithm）.展开更多
为提高基于行驶工况预测油耗的准确性,创新性地提出针对重型商用车细分市场构建行驶工况的研究思路。为验证此研究思路的必要性与合理性,以日用工业品市场为例,对国六商用车行驶工况进行大数据分析。依托车载天行健智能网联系统采集了...为提高基于行驶工况预测油耗的准确性,创新性地提出针对重型商用车细分市场构建行驶工况的研究思路。为验证此研究思路的必要性与合理性,以日用工业品市场为例,对国六商用车行驶工况进行大数据分析。依托车载天行健智能网联系统采集了该市场中3000辆国六系列半挂牵引车的用户行驶数据,通过数据清洗、运动学片段切分、数据降维、工况合成等一系列步骤,构建了3条代表性工况。以此为基础,采用AVL Cruise软件构建仿真模型,基于所构建工况预测目标市场的用户油耗,并与基于中国重型商用车瞬态工况(China world transient vehicle cycle,C-WTVC)和中国重型半牵引车行驶工况(China heavy-duty commercial vehicle test cycle for tractor-trailer,CHTC-TT)的预测结果进行对比。结果表明,与同车型国家标准工况(C-WTVC和CHTC-TT)相比,构建的日用工业品细分市场工况与目标市场下大数据统计的实际运行特征更接近,特征参数平均相对误差分别减少32.97个百分点和18.67个百分点,且能够更精确地预测用户使用油耗,预测精度分别提高7%和4%。针对重型商用车细分市场构建行驶工况能更精确地刻画目标市场用户的车辆使用特征,提高了用户油耗的预测精度。展开更多
基金funding support from the National Natural Science Foundation of China(Grant Nos.42077262 and 42077261).
文摘A complete road-soft ground model is established in this paper to study the dynamic responses caused by vehicle loads and/or daily temperature variation.A dynamic thermo-elastic model is applied to capturing the behavior of the rigid pavement,the base course,and the subgrade,while the soft ground is characterized using a dynamic thermo-poroelastic model.Solutions to the road-soft ground system are derived in the Laplace-Hankel transform domain.The time domain solutions are obtained using an integration approach.The temperature,thermal stress,pore water pressure,and displacement responses caused by the vehicle load and the daily temperature variation are presented.Results show that obvious temperature change mainly exists within 0.3 m of the road when subjected to the daily temperature variation,whereas the stress responses can still be found in deeper places because of the thermal swelling/shrinkage deformation within the upper road structures.Moreover,it is important to consider the coupling effects of the vehicle load and the daily temperature variation when calculating the dynamic responses inside the road-soft ground system.
文摘ELD （economic load dispatch） problem is one of the essential issues in power system operation. The objective of solving ELD problem is to allocate the generation output of the committed generating units. The main contribution of this work is to solve the ELD problem concerned with daily load pattern. The proposed solution technique, developed based PSO （particle swarm optimization） algorithm, is applied to search for the optimal schedule of all generations units that can supply the required load demand at minimum fuel cost while satisfying all unit and system operational constraints. The performance of the developed methodology is demonstrated by case studies in test system of six-generation units. The results obtained from the PSO are compared to those achieved from other approaches, such as QP （quadratic programming）, and GA （genetic algorithm）.
文摘为提高基于行驶工况预测油耗的准确性,创新性地提出针对重型商用车细分市场构建行驶工况的研究思路。为验证此研究思路的必要性与合理性,以日用工业品市场为例,对国六商用车行驶工况进行大数据分析。依托车载天行健智能网联系统采集了该市场中3000辆国六系列半挂牵引车的用户行驶数据,通过数据清洗、运动学片段切分、数据降维、工况合成等一系列步骤,构建了3条代表性工况。以此为基础,采用AVL Cruise软件构建仿真模型,基于所构建工况预测目标市场的用户油耗,并与基于中国重型商用车瞬态工况(China world transient vehicle cycle,C-WTVC)和中国重型半牵引车行驶工况(China heavy-duty commercial vehicle test cycle for tractor-trailer,CHTC-TT)的预测结果进行对比。结果表明,与同车型国家标准工况(C-WTVC和CHTC-TT)相比,构建的日用工业品细分市场工况与目标市场下大数据统计的实际运行特征更接近,特征参数平均相对误差分别减少32.97个百分点和18.67个百分点,且能够更精确地预测用户使用油耗,预测精度分别提高7%和4%。针对重型商用车细分市场构建行驶工况能更精确地刻画目标市场用户的车辆使用特征,提高了用户油耗的预测精度。
