Accidental or frequent shift often occurs when the shifting rule is built based on traditional two parameters （i.e., velocity and throttle）, because the speed of engine varies slower than change of throttle opening....Accidental or frequent shift often occurs when the shifting rule is built based on traditional two parameters （i.e., velocity and throttle）, because the speed of engine varies slower than change of throttle opening. Currently, modifying shift point velocity value or throttle by throttle change rate is one of common methods, but the results are not so satisfactory in some working condition such as uphill. The reason is that these methods merely consider throttle change rate which is not enough for a car driving in driver-vehicle-road environment system. So a novel fuzzy control modification strategy is proposed to avoid or reduce those abnormal shift actions. It can adjust shifting rule by the change rate of throttle, current gear position and road environment information, while different gear position and driving environment get corresponding modification value. In order to compare the results of shifting actions, fuel consumption and braking distance, emergent braking in level road and extra-urban driving cycle（EUDC） working conditions with fuzzy shifting schedule modification strategy are simulated digitally. Furthermore, a hardware-in-the-loop simulation platform is introduced to verify its effect in slope road condition according to the ON/OFF numbers of solenoid valve in hydraulic system. The simulation results show that the problem of unexpected shift in those working conditions may be resolved by fuzzy modification strategy. At last, it is concluded that although there is some slight decline in power performance in uphill situation, this fuzzy modification strategy could correctly identify slope of road, decrease braking distance, improve vehicle comfort and fuel economy effectively and prolong the life of clutch system. So, this fuzzy logic shifting strategy provides important references for vehicle intelligent shifting schedule.展开更多
Fuzzy logic is an approach which deals with the incomplete information to handle the imperfect knowledge. In the present research paper we have proposed a new approach that can handle the imperfect knowledge, in a bro...Fuzzy logic is an approach which deals with the incomplete information to handle the imperfect knowledge. In the present research paper we have proposed a new approach that can handle the imperfect knowledge, in a broader way that we will consider the unfavourable case also as the intuitionistic fuzzy logic does. The mediative fuzzy logic is an extensive approach of intuitionistic fuzzy logic, which provides a solution, when there is a contradiction in the expert knowledge for favourable as well as unfavourable cases. The purpose of the present paper is to design a mediative fuzzy inference system based Sugeno-TSK model for the diagnosis of heart disease. Our proposed method is the extension of Sugeno-TSK fuzzy logic controller in the form of Sugeno-TSK mediative fuzzy logic controller.展开更多
基金supported by Science and Technology Commission Shanghai Municipality (Grant No. 06dz1102, Grant No. 08dz1150401)
文摘Accidental or frequent shift often occurs when the shifting rule is built based on traditional two parameters （i.e., velocity and throttle）, because the speed of engine varies slower than change of throttle opening. Currently, modifying shift point velocity value or throttle by throttle change rate is one of common methods, but the results are not so satisfactory in some working condition such as uphill. The reason is that these methods merely consider throttle change rate which is not enough for a car driving in driver-vehicle-road environment system. So a novel fuzzy control modification strategy is proposed to avoid or reduce those abnormal shift actions. It can adjust shifting rule by the change rate of throttle, current gear position and road environment information, while different gear position and driving environment get corresponding modification value. In order to compare the results of shifting actions, fuel consumption and braking distance, emergent braking in level road and extra-urban driving cycle（EUDC） working conditions with fuzzy shifting schedule modification strategy are simulated digitally. Furthermore, a hardware-in-the-loop simulation platform is introduced to verify its effect in slope road condition according to the ON/OFF numbers of solenoid valve in hydraulic system. The simulation results show that the problem of unexpected shift in those working conditions may be resolved by fuzzy modification strategy. At last, it is concluded that although there is some slight decline in power performance in uphill situation, this fuzzy modification strategy could correctly identify slope of road, decrease braking distance, improve vehicle comfort and fuel economy effectively and prolong the life of clutch system. So, this fuzzy logic shifting strategy provides important references for vehicle intelligent shifting schedule.
文摘Fuzzy logic is an approach which deals with the incomplete information to handle the imperfect knowledge. In the present research paper we have proposed a new approach that can handle the imperfect knowledge, in a broader way that we will consider the unfavourable case also as the intuitionistic fuzzy logic does. The mediative fuzzy logic is an extensive approach of intuitionistic fuzzy logic, which provides a solution, when there is a contradiction in the expert knowledge for favourable as well as unfavourable cases. The purpose of the present paper is to design a mediative fuzzy inference system based Sugeno-TSK model for the diagnosis of heart disease. Our proposed method is the extension of Sugeno-TSK fuzzy logic controller in the form of Sugeno-TSK mediative fuzzy logic controller.
