The performance of the power assist, global optimization solved by dynamic programming （DP） method, Chery and Insight control strategies are analyzed using the mild parallel hybrid electric vehicle （PHEV） model ba...The performance of the power assist, global optimization solved by dynamic programming （DP） method, Chery and Insight control strategies are analyzed using the mild parallel hybrid electric vehicle （PHEV） model based on Insight structure. The influence of the four control strategies to the load power of the electric motor system used on parallel hybrid electric vehicle is studied. It is found that 80 percent of the motor load power points are under 1/5 of the electric peak power. The motor load power of the power assist control strategy is distributed in the widest range during generating operation, and the motor load power of the global optimization control strategy has the smallest one.展开更多
Computer-aided process planning （CAPP） is an essential component of computer integrated manufacturing （CIM） system. A good process plan can be obtained by optimizing two elements, namely, operation sequence and th...Computer-aided process planning （CAPP） is an essential component of computer integrated manufacturing （CIM） system. A good process plan can be obtained by optimizing two elements, namely, operation sequence and the machining parameters of machine, tool and tool access direction （TAD） for each operation. This paper proposes a novel optimization strategy for process planning that considers different dimensions of the problem in parallel. A multi-dimensional tabu search （MDTS） algo-rithm based on this strategy is developed to optimize the four dimensions of a process plan, namely, operation sequence （OperSeq）, machine sequence （MacSeq）, tool sequence （TooISeq） and tool approach direction sequence （TADSeq）, sequentially and iteratively. In order to improve its efficiency and stability, tabu search, which is incorporated into the proposed MDTS al- gorithm, is used to optimize each component of a process plan, and some neighbourhood strategies for different components are presented for this tabu search algorithm. The proposed MDTS algorithm is employed to test four parts with different numbers of operations taken from the literature and compared with the existing algorithms like genetic algorithm （GA）, simulated annealing （SA）, tabu search （TS） and particle swarm optimization （PSO）. Experimental results show that the developed algo-rithm outperforms these algorithms in terms of solution quality and efficiency.展开更多
文摘The performance of the power assist, global optimization solved by dynamic programming （DP） method, Chery and Insight control strategies are analyzed using the mild parallel hybrid electric vehicle （PHEV） model based on Insight structure. The influence of the four control strategies to the load power of the electric motor system used on parallel hybrid electric vehicle is studied. It is found that 80 percent of the motor load power points are under 1/5 of the electric peak power. The motor load power of the power assist control strategy is distributed in the widest range during generating operation, and the motor load power of the global optimization control strategy has the smallest one.
基金supported by the State Key Program of National Natural Science Foundation of China (Grant No. 51035001)National Natural Science Foundation of China (Grant Nos. 50825503, 50875101)
文摘Computer-aided process planning （CAPP） is an essential component of computer integrated manufacturing （CIM） system. A good process plan can be obtained by optimizing two elements, namely, operation sequence and the machining parameters of machine, tool and tool access direction （TAD） for each operation. This paper proposes a novel optimization strategy for process planning that considers different dimensions of the problem in parallel. A multi-dimensional tabu search （MDTS） algo-rithm based on this strategy is developed to optimize the four dimensions of a process plan, namely, operation sequence （OperSeq）, machine sequence （MacSeq）, tool sequence （TooISeq） and tool approach direction sequence （TADSeq）, sequentially and iteratively. In order to improve its efficiency and stability, tabu search, which is incorporated into the proposed MDTS al- gorithm, is used to optimize each component of a process plan, and some neighbourhood strategies for different components are presented for this tabu search algorithm. The proposed MDTS algorithm is employed to test four parts with different numbers of operations taken from the literature and compared with the existing algorithms like genetic algorithm （GA）, simulated annealing （SA）, tabu search （TS） and particle swarm optimization （PSO）. Experimental results show that the developed algo-rithm outperforms these algorithms in terms of solution quality and efficiency.
