This manuscript presents a modified algorithm to extract depth information from stereo-vision acquisitions using a correlation based approaches. The main implementation of the proposed method is in the area of autonom...This manuscript presents a modified algorithm to extract depth information from stereo-vision acquisitions using a correlation based approaches. The main implementation of the proposed method is in the area of autonomous Pick & Place, using a robotic manipulator. Current vision-guided robotics is still based on a priori training and teaching steps, and still suffers from long response time. This study uses a stereo triangulation setup where two Charged Coupled Devices CCDs are arranged to acquire the scene from two different perspectives. The study discusses the details to calculate the depth using a correlation matching routine which programmed using a Square Sum Difference SSD algorithm to search for the corresponding points from the left and the right images. The SSD is further modified using an adjustable Region Of Interest ROI along with a center of gravity based calculations. Furthermore, the two perspective images are rectified to reduce the required processing time. The reported error in depth using the modified SSD method is found to be around 1.2 mm.展开更多
In this paper, the hardness property during natural age hardening phenomenon for aluminum based alloy has been studied. Different factors play role in aging hardening of aluminum. In this study, the chosen factors wer...In this paper, the hardness property during natural age hardening phenomenon for aluminum based alloy has been studied. Different factors play role in aging hardening of aluminum. In this study, the chosen factors were percentages of copper and nickel in aluminum alloys. The specimens were manufactured using casting process, and then heat treatment was carried out for all produced samples together at 550 °C for 3 h before quenching in water. Finally, the specimens were left at room temperature for 936 hours (39days) to allow solute atoms to defuse and form coherent phases to allow the age hardening to take place. The results show that the hardness increased with time in the first 300 hour after the quenching time, and then it remained constant for the rest of the 936 hours. Furthermore, the hardness did not drop until the end of 936 hours which means the over-aging status was not achieved. To get full analysis of the natural aging, design of experiment technique was used to study the effect of %Cu, %Ni and aging time.展开更多
In recent years, aluminum-matrix composites (AMCs) have been widely used to replace cast iron in aerospace and automotive industries. Machining of these composite materials requires better understanding of cutting pro...In recent years, aluminum-matrix composites (AMCs) have been widely used to replace cast iron in aerospace and automotive industries. Machining of these composite materials requires better understanding of cutting processes re- garding accuracy and efficiency. This study addresses the modeling of the machinability of self-lubricated aluminum /alumina/graphite hybrid composites synthesized by the powder metallurgy method. In this study, multiple regression analysis (MRA) and artificial neural networks (ANN) were used to investigate the influence of some parameters on the thrust force and torque in the drilling processes of self-lubricated hybrid composite materials. The models were identi- fied by using cutting speed, feed, and volume fraction of the reinforcement particles as input data and the thrust force and torque as the output data. A comparison between two prediction methods was developed to compare the prediction accuracy. ANNs showed better predictability results compared to MRA due to the nonlinearity nature of ANNs. The statistical analysis accompanied with artificial neural network results showed that Al2O3, Gr and cutting feed (f) were the most significant parameters on the drilling process, while spindle speed seemed insignificant. Since the spindle speed was insignificant, it directed us to set it either at the highest spindle speed to obtain high material removal rate or at the lowest spindle speed to prolong the tool life depending on the need for the application.展开更多
A Continuously Variable Transmission (CVT) is a type of transmissions that provides a continuous range of speed ratios, thus it allows increasing the overall powertrain efficiency by running the engine at the optimal ...A Continuously Variable Transmission (CVT) is a type of transmissions that provides a continuous range of speed ratios, thus it allows increasing the overall powertrain efficiency by running the engine at the optimal operating points. This paper investigates implementing a model based hydraulic pressure controller to achieve the desired CVT gear ratio. A map of desired gear ratios was estimated using the Optimal Operating Line (OOL) strategy, which minimizes the engine fuel consumption according to a defined cost function and a set of systems constraints. The controller was implemented in a complete vehicle model that includes driver, powertrain and road load models. The model was subjected to two different driving cycles and the results demonstrate the effectiveness of the control strategy and the pressure controller in keeping the engine at the most efficient operating regions.展开更多
This paper presents a decentralized fuel efficient model predictive control(MPC) strategy for a group of connected vehicles incorporating vertical vibration. To capture the vehicle vibration dynamics, the dynamics of ...This paper presents a decentralized fuel efficient model predictive control(MPC) strategy for a group of connected vehicles incorporating vertical vibration. To capture the vehicle vibration dynamics, the dynamics of the suspension system is integrated with the longitudinal dynamics of the vehicle. Furthermore, a MPC framework with finite time horizon is formulated to calculate the optimal velocity profile that compromises fuel economy, mobility and ride comfort for every individual vehicle with the safety and physical constraints considered. In the MPC framework, the target velocity is calculated using signal phase and timing(SPAT)information to reduce the number of stoppage at red lights, and the vertical acceleration is calculated parallel to the calculation of the fuel consumption. The MPC optimal problem is solved with fast-MPC approach which enhances the computational efficiency via exploiting the structure of the control system and approximate methods. Simulation studies are conducted over different SPATs and connectivity penetration rates and the results validate the advantages of the proposed control architecture.展开更多
This paper presents an optimized equivalent consumption minimization strategy(ECMS) for four-wheel-drive(4 WD) hybrid electric vehicles(HEVs) incorporating vehicle connectivity. In order to be applicable to the 4 WD a...This paper presents an optimized equivalent consumption minimization strategy(ECMS) for four-wheel-drive(4 WD) hybrid electric vehicles(HEVs) incorporating vehicle connectivity. In order to be applicable to the 4 WD architecture, the ECMS is designed based on a rule-based strategy and used under the condition that a certain propulsion mode is activated. Assuming that a group of 4 WD HEVs are connected and position information can be shared with each other, we formulate a decentralized model predictive control(MPC) framework that compromises fuel efficiency, mobility, and inter-vehicle distance to optimize the velocity profile of each individual vehicle. Based on the optimized velocity profile, an optimization problem considering both fuel economy and battery state of charge(SOC) sustainability is formulated to optimize the equivalent factors(EFs) of the ECMS for HEVs over an appropriate time window. MATLAB User Datagram Protocol(UDP) is used in the codes run on multiple computers to simulate the wireless communication among vehicles, which share position information via UDP-based communication, and dSPACE is used as a software-in-the-loop platform for the simulation of the optimized ECMS. Simulation results validate the control effectiveness of the proposed method.展开更多
An engine-map-based predictive fuel-efficient control strategy for a group of connected vehicles is presented. A decentralizedmodel predictive control framework is formulated to predict the optimal velocity profile th...An engine-map-based predictive fuel-efficient control strategy for a group of connected vehicles is presented. A decentralizedmodel predictive control framework is formulated to predict the optimal velocity profile that compromises fuel economy andmobility while guaranteeing the safety of each vehicle. In the model predictive control framework, an engine-map-based fuelconsumption model is established by implementing a backward conventional vehicle model in the cost function. Moreover,the cost function is normalized by dividing each term by its reference value. An extra cost is added to the safety term when thedistance between adjacent vehicles drops to a critical value to guarantee vehicle safety, while another extra cost is consideredfor the velocity tracking term to prevent the violation of traffic rules. The results of simulation show the effectiveness of theproposed control method.展开更多
With the combination of engine and two electric machines, the power split device allows higher efficiency of the engine. The operation modes of a power split HEV are analyzed, and the system dynamic model is establish...With the combination of engine and two electric machines, the power split device allows higher efficiency of the engine. The operation modes of a power split HEV are analyzed, and the system dynamic model is established for HEV forward simulation and controller design. Considering the fact that the operation modes of the HEV are event-driven and the system dynamics is continuous time-driven for each mode, the structure of the controller is built and described with the hybrid automaton control theory. In this control structure, the mode selection process is depicted by the finite state machine （FSM）. The multi-mode switch controller is designed to realize power distribution. Furthermore, the vehicle mode operations are optimized, and the nonlinear model predictive control （NMPC） strategy is applied by implementing dynamic programming （DP） in the finite pre- diction horizon. Comparative simulation results demonstrate that the hybrid control structure is effective and feasible for HEV energy management design. The NMPC optimal strategy is superior in improving fuel economy.展开更多
文摘This manuscript presents a modified algorithm to extract depth information from stereo-vision acquisitions using a correlation based approaches. The main implementation of the proposed method is in the area of autonomous Pick & Place, using a robotic manipulator. Current vision-guided robotics is still based on a priori training and teaching steps, and still suffers from long response time. This study uses a stereo triangulation setup where two Charged Coupled Devices CCDs are arranged to acquire the scene from two different perspectives. The study discusses the details to calculate the depth using a correlation matching routine which programmed using a Square Sum Difference SSD algorithm to search for the corresponding points from the left and the right images. The SSD is further modified using an adjustable Region Of Interest ROI along with a center of gravity based calculations. Furthermore, the two perspective images are rectified to reduce the required processing time. The reported error in depth using the modified SSD method is found to be around 1.2 mm.
文摘In this paper, the hardness property during natural age hardening phenomenon for aluminum based alloy has been studied. Different factors play role in aging hardening of aluminum. In this study, the chosen factors were percentages of copper and nickel in aluminum alloys. The specimens were manufactured using casting process, and then heat treatment was carried out for all produced samples together at 550 °C for 3 h before quenching in water. Finally, the specimens were left at room temperature for 936 hours (39days) to allow solute atoms to defuse and form coherent phases to allow the age hardening to take place. The results show that the hardness increased with time in the first 300 hour after the quenching time, and then it remained constant for the rest of the 936 hours. Furthermore, the hardness did not drop until the end of 936 hours which means the over-aging status was not achieved. To get full analysis of the natural aging, design of experiment technique was used to study the effect of %Cu, %Ni and aging time.
文摘In recent years, aluminum-matrix composites (AMCs) have been widely used to replace cast iron in aerospace and automotive industries. Machining of these composite materials requires better understanding of cutting processes re- garding accuracy and efficiency. This study addresses the modeling of the machinability of self-lubricated aluminum /alumina/graphite hybrid composites synthesized by the powder metallurgy method. In this study, multiple regression analysis (MRA) and artificial neural networks (ANN) were used to investigate the influence of some parameters on the thrust force and torque in the drilling processes of self-lubricated hybrid composite materials. The models were identi- fied by using cutting speed, feed, and volume fraction of the reinforcement particles as input data and the thrust force and torque as the output data. A comparison between two prediction methods was developed to compare the prediction accuracy. ANNs showed better predictability results compared to MRA due to the nonlinearity nature of ANNs. The statistical analysis accompanied with artificial neural network results showed that Al2O3, Gr and cutting feed (f) were the most significant parameters on the drilling process, while spindle speed seemed insignificant. Since the spindle speed was insignificant, it directed us to set it either at the highest spindle speed to obtain high material removal rate or at the lowest spindle speed to prolong the tool life depending on the need for the application.
文摘A Continuously Variable Transmission (CVT) is a type of transmissions that provides a continuous range of speed ratios, thus it allows increasing the overall powertrain efficiency by running the engine at the optimal operating points. This paper investigates implementing a model based hydraulic pressure controller to achieve the desired CVT gear ratio. A map of desired gear ratios was estimated using the Optimal Operating Line (OOL) strategy, which minimizes the engine fuel consumption according to a defined cost function and a set of systems constraints. The controller was implemented in a complete vehicle model that includes driver, powertrain and road load models. The model was subjected to two different driving cycles and the results demonstrate the effectiveness of the control strategy and the pressure controller in keeping the engine at the most efficient operating regions.
基金supported by National Hi-Tech Research and Development Program of China(Grant Nos.2015BAG17B04&2013BAG08B01)U.S.National Science Foundation(Grant No.1544910)U.S.Department of Energy GATE Program and China Scholarship Council
文摘This paper presents a decentralized fuel efficient model predictive control(MPC) strategy for a group of connected vehicles incorporating vertical vibration. To capture the vehicle vibration dynamics, the dynamics of the suspension system is integrated with the longitudinal dynamics of the vehicle. Furthermore, a MPC framework with finite time horizon is formulated to calculate the optimal velocity profile that compromises fuel economy, mobility and ride comfort for every individual vehicle with the safety and physical constraints considered. In the MPC framework, the target velocity is calculated using signal phase and timing(SPAT)information to reduce the number of stoppage at red lights, and the vertical acceleration is calculated parallel to the calculation of the fuel consumption. The MPC optimal problem is solved with fast-MPC approach which enhances the computational efficiency via exploiting the structure of the control system and approximate methods. Simulation studies are conducted over different SPATs and connectivity penetration rates and the results validate the advantages of the proposed control architecture.
基金supported by the National Hi-Tech Research and Development Program of China(Grant No.2015BAG17B04)China Scholarship Council(Grant No.201506690009)U.S.GATE Program
文摘This paper presents an optimized equivalent consumption minimization strategy(ECMS) for four-wheel-drive(4 WD) hybrid electric vehicles(HEVs) incorporating vehicle connectivity. In order to be applicable to the 4 WD architecture, the ECMS is designed based on a rule-based strategy and used under the condition that a certain propulsion mode is activated. Assuming that a group of 4 WD HEVs are connected and position information can be shared with each other, we formulate a decentralized model predictive control(MPC) framework that compromises fuel efficiency, mobility, and inter-vehicle distance to optimize the velocity profile of each individual vehicle. Based on the optimized velocity profile, an optimization problem considering both fuel economy and battery state of charge(SOC) sustainability is formulated to optimize the equivalent factors(EFs) of the ECMS for HEVs over an appropriate time window. MATLAB User Datagram Protocol(UDP) is used in the codes run on multiple computers to simulate the wireless communication among vehicles, which share position information via UDP-based communication, and dSPACE is used as a software-in-the-loop platform for the simulation of the optimized ECMS. Simulation results validate the control effectiveness of the proposed method.
基金the National Hi-Tech Research and Development Program of China(“863”Project)(Grant No.2015BAG17B04)National Natural Science Foundation of China(Grant No.51875149)China Scholarship Council(Grant No.201506690009)and U.S.Department of Energy GATE program.
文摘An engine-map-based predictive fuel-efficient control strategy for a group of connected vehicles is presented. A decentralizedmodel predictive control framework is formulated to predict the optimal velocity profile that compromises fuel economy andmobility while guaranteeing the safety of each vehicle. In the model predictive control framework, an engine-map-based fuelconsumption model is established by implementing a backward conventional vehicle model in the cost function. Moreover,the cost function is normalized by dividing each term by its reference value. An extra cost is added to the safety term when thedistance between adjacent vehicles drops to a critical value to guarantee vehicle safety, while another extra cost is consideredfor the velocity tracking term to prevent the violation of traffic rules. The results of simulation show the effectiveness of theproposed control method.
基金supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)the National Natural Science Foundation of China(Grant Nos.51475213&51305167)the Scientific Research Innovation Projects of Jiangsu Province(Grant No.KYLX_1022)
文摘With the combination of engine and two electric machines, the power split device allows higher efficiency of the engine. The operation modes of a power split HEV are analyzed, and the system dynamic model is established for HEV forward simulation and controller design. Considering the fact that the operation modes of the HEV are event-driven and the system dynamics is continuous time-driven for each mode, the structure of the controller is built and described with the hybrid automaton control theory. In this control structure, the mode selection process is depicted by the finite state machine （FSM）. The multi-mode switch controller is designed to realize power distribution. Furthermore, the vehicle mode operations are optimized, and the nonlinear model predictive control （NMPC） strategy is applied by implementing dynamic programming （DP） in the finite pre- diction horizon. Comparative simulation results demonstrate that the hybrid control structure is effective and feasible for HEV energy management design. The NMPC optimal strategy is superior in improving fuel economy.
