Research on Selection and Matching Optimization of Automobile Drive Train

2012 ◽  
Vol 160 ◽  
pp. 346-350
Author(s):  
Guang Hui Zhang
Keyword(s):  
Model Selection ◽  
Test Data ◽  
Fuel Economy ◽  
Comprehensive Evaluation ◽  
Matching Condition ◽  
Automotive Engine ◽  
Complete Vehicle ◽  
Simulation Results ◽  
Final Drive ◽  
The Given

This paper studies the evaluation methods on model selection, matching scheme and matching program of automotive engine, transmission and final drive. Based on the given matching condition of the engine and transmission, the complete vehicle parameters, engine stand test data and drive line parameter, the program can quickly conduct selection and matching to the engine and drive line in the database and display the simulation results of the vehicle power, fuel economy and emissions corresponding to the each matching program, with which to do comprehensive evaluation to the corresponding matching program, provide a reference for users with drive line match and design and lay foundation for software system completion.

scholarly journals Analytical Investigation of Tension Loaded Deformed Rebar Anchors in Concrete

CivilEng ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 442-458
Author(s):  
Sandip Chhetri ◽  
Rachel A. Chicchi
Keyword(s):  
Test Data ◽  
Parametric Study ◽  
Failure Modes ◽  
Experimental Testing ◽  
Analytical Investigation ◽  
Failure Behavior ◽  
Capacity Design ◽  
Simulation Results

Experimental testing of deformed rebar anchors (DRAs) has not been performed extensively, so there is limited test data to understand their failure behavior. This study aims to expand upon these limited tests and understand the behavior of these anchors, when loaded in tension. Analytical benchmark models were created using available test data and a parametric study of deformed rebar anchors was performed. Anchor diameter, spacing, embedment, and number of anchors were varied for a total of 49 concrete breakout simulations. The different failure modes of anchors were predicted analytically, which showed that concrete breakout failure is prominent in the DRA groups. The predicted concrete breakout values were consistent with mean and 5% fractile concrete capacities determined from the ACI concrete capacity design (CCD) method. The 5% fractile factor determined empirically from the simulation results was kc = 26. This value corresponds closely with kc = 24 specified in ACI 318-19 and ACI 349-13 for cast-in place anchors. The analysis results show that the ACI CCD formula can be conservatively used to design DRAs loaded in tension by applying a kc factor no greater than 26.

Development of Advanced CNC Interpolation Algorithm With Consideration of Command and Dynamic Errors

2015 ◽  
Author(s):  
Meng-Shiun Tsai ◽  
Ying-Che Huang
Keyword(s):  
The Other ◽  
Contour Error ◽  
Interpolation Algorithm ◽  
Interpolation Scheme ◽  
Error Equation ◽  
The Past ◽  
Cnc Interpolation ◽  
Dynamic Errors ◽  
Simulation Results ◽  
The Given

In this paper, an integrated acceleration/deceleration with dynamics interpolation scheme is proposed to confine the maximum contour error at the junction of linear junction. The dynamic contour error equation is derived analytically and then it is utilized for the interpolation design. Based on the derived formulations which could predict the command and dynamic errors, the advanced interpolation design could adjust the connecting velocity of the two blocks to confine the overall contour errors under the given tolerance. Simulation results validate the proposed algorithm can achieve higher accurate trajectory as compared to the other interpolation algorithm proposed in the past.

An adaptive equivalent consumption minimization strategy considering catalyst temperature for plug-in hybrid electric vehicle

2021 ◽  
pp. 095440702110434
Author(s):  
Tao Deng ◽  
Ke Zhao ◽  
Haoyuan Yu
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicle ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Test Procedure ◽  
Catalyst Temperature ◽  
Equivalent Factor ◽  
Simulation Results ◽  
Hybrid Electric ◽  
Equivalent Consumption Minimization Strategy

In the process of sufficiently considering fuel economy of plug-in hybrid electric vehicle (PHEV), the working time of engine will be reduced accordingly. The increased frequency that the three-way catalytic converter (TWCC) works in abnormal operating temperature will lead to the increasing of emissions. This paper proposes the equivalent consumption minimization strategy (ECMS) to ensure the catalyst temperature of PHEV can work in highly efficient areas, and the influence of catalyst temperature on fuel economy and emissions is considered. The simulation results show that the fixed equivalent factor of ECMS has great limitations for the underutilized battery power and the poor fuel economy. In order to further reduce fuel consumption and keep the emission unchanged, an equivalent factor map based on initial state of charge (SOC) and vehicle mileage is established by the genetic algorithm. Furthermore, an Adaptive changing equivalent factor is achieved by using the following strategy of SOC trajectory. Ultimately, adaptive equivalent consumption minimization strategy (A-ECMS) considering catalyst temperature is proposed. The simulation results show that compared with ordinary ECMS, HC, CO, and NOX are reduced by 14.6%, 20.3%, and 25.8%, respectively, which effectively reduces emissions. But the fuel consumption is increased by only 2.3%. To show that the proposed method can be used in actual driving conditions, it is tested on the World Light Vehicle Test Procedure (WLTC).

scholarly journals Economic Environmental Dispatch of Wind Integrated Thermal Power System

2020 ◽  
Vol 8 (6) ◽  
pp. 5186-5192
Keyword(s):  
Genetic Algorithm ◽  
Power Plant ◽  
Thermal Power ◽  
Nsga Ii ◽  
Strength Pareto Evolutionary Algorithm ◽  
Experimental Constraint ◽  
Thermal Power System ◽  
Power Plant Operation ◽  
Simulation Results ◽  
The Given

In electric power plant operation, Economic Environmental Dispatch (EED) of a thermal-wind is a significant chore to involve allocation of production amongst the running units so the price, NOx extraction status and SO2 extraction status are enhanced concurrently whilst gratifying each and every experimental constraint. This is an exceedingly controlled multiobjective optimizing issue concerning contradictory objectives having Primary and Secondary constraints. For the given work, a Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is recommended for taking care of EED issue. In simulation results that are obtained by applying the two test systems on the proposed scheme have been evaluated against Strength Pareto Evolutionary Algorithm 2 (SPEA 2).

scholarly journals Improving COVID-19 Testing Efficiency using Guided Agglomerative Sampling

2020 ◽  
Author(s):  
Fayyaz Minhas ◽  
Dimitris Grammatopoulos ◽  
Lawrence Young ◽  
Imran Amin ◽  
David Snead ◽  
...  
Keyword(s):  
Large Scale ◽  
Resource Constraints ◽  
Large Population ◽  
Sampling Strategy ◽  
Population Surveillance ◽  
Large Scale Testing ◽  
Scale Population ◽  
Simulation Results ◽  
The Given ◽  
Test Outcomes

AbstractOne of the challenges in the current COVID-19 crisis is the time and cost of performing tests especially for large-scale population surveillance. Since, the probability of testing positive in large population studies is expected to be small (<15%), therefore, most of the test outcomes will be negative. Here, we propose the use of agglomerative sampling which can prune out multiple negative cases in a single test by intelligently combining samples from different individuals. The proposed scheme builds on the assumption that samples from the population may not be independent of each other. Our simulation results show that the proposed sampling strategy can significantly increase testing capacity under resource constraints: on average, a saving of ~40% tests can be expected assuming a positive test probability of 10% across the given samples. The proposed scheme can also be used in conjunction with heuristic or Machine Learning guided clustering for improving the efficiency of large-scale testing further. The code for generating the simulation results for this work is available here: https://github.com/foxtrotmike/AS.

scholarly journals A New Decentralized Approach of Multiagent Cooperative Pursuit Based on the Iterated Elimination of Dominated Strategies Model

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Mohammed El Habib Souidi ◽  
Songhao Piao
Keyword(s):  
Game Theory ◽  
Coalition Formation ◽  
Decision Process ◽  
Pursuit Evasion ◽  
Dominated Strategies ◽  
Markov Decision ◽  
Simulation Results ◽  
The Given ◽  
Dynamic Formation ◽  
Motion Strategy

Game Theory is a promising approach to acquire coalition formations in multiagent systems. This paper is focused on the importance of the distributed computation and the dynamic formation and reformation of pursuit groups in pursuit-evasion problems. In order to address this task, we propose a decentralized coalition formation algorithm based on the Iterated Elimination of Dominated Strategies (IEDS). This Game Theory process is common to solve problems requiring the withdrawal of dominated strategies iteratively. Furthermore, we have used the Markov Decision Process (MDP) principles to control the motion strategy of the agents in the environment. The simulation results demonstrate the feasibility and the validity of the given approach in comparison with different decentralized methods.

Simulation of a Hydropneumatic Suspension for Agricultural Working Vehicles

2021 ◽  
pp. 268-287
Author(s):  
Nicola Bosso ◽  
Nicolò Zampieri ◽  
Aurelio Somà ◽  
Francesco Mocera ◽  
Emanuele Conte
Keyword(s):  
Kinematic Model ◽  
Suspension System ◽  
Vehicle Performance ◽  
Vehicle Simulation ◽  
Complete Vehicle ◽  
Simulation Results

The chapter shows the study and simulation of a hydropneumatic suspension to be adopted for a telescopic handler vehicle. The hydropneumatic suspension system with independent wheels and with quadrilateral architecture has been studied to improve comfort and productivity of the existing vehicle, which has a suspended rigid axle on the front and a rigid axle on the rear, limiting the comfort and the grip. After the choice of the architecture and the kind of suspension, the chapter shows the design of the suspension kinematics. The optimization of the characteristic angles of the suspension has been performed using Adams/Car and Adams/Insight. The kinematic model optimized is subsequently reproduced in Adams/View to simulate the dynamics of the complete vehicle. Simulation results are used to evaluate vehicle performance in terms of comfort and stability according to the methods proposed by the standards.

scholarly journals Optimized Combination of Local Beams for Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 633
Author(s):  
Semyoung Oh ◽  
Young-Dam Kim ◽  
Daejin Park
Keyword(s):  
Signal To Noise Ratio ◽  
Wireless Sensor ◽  
Linear Arrays ◽  
Wave Channel ◽  
Average Improvement ◽  
Simulation Results ◽  
Noise Ratio ◽  
The Given ◽  
Single Objective ◽  
Average Interference

This paper proposes an optimization algorithm to determine the optimal coherent combination candidates of distributed local beams in a wireless sensor network. The beams are generated from analog uniform linear arrays of nodes and headed toward the random directions due to the irregular surface where the nodes are mounted. Our algorithm is based on one of the meta-heuristic schemes (i.e., the single-objective simulated annealing) and designed to solve the objective of minimizing the average interference-to-noise ratio (INR) under the millimeter wave channel, which leads to the reduction of sidelobes. The simulation results show that synthesizing the beams on the given system can form a deterministic mainlobe with considerable and unpredictable sidelobes in undesired directions, and the proposed algorithm can decrease the average INR (i.e., the average improvement of 12.2 dB and 3.1 dB are observed in the directions of π 6 and 2 π 3 , respectively) significantly without the severe loss of signal-to-noise ratio (SNR) in the desired direction.

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