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Siemens AG simcenter amesim environment
Simcenter Amesim Environment, supplied by Siemens AG, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/amesim/simcenter+amesim/10__1016_slash_j__applthermaleng__2024__124663-317-12-15
Average 90 stars, based on 1 article reviews
simcenter amesim environment - by Bioz Stars, 2026-09
90/100 stars

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Related Articles

Control:

Article Title: Analysis of a Measurement Method and Test System for Pressure Change Rates in Commercial Vehicle Brake Chambers.
Article Snippet: .. Liang, C. et al. [11] established the joint simulation platform of Matlab (MathWorks.Inc, Natick, MA, USA) and AMESim (SIEMENS AG, Berlin and Munich, Germany), from which the relationship curves between the component parameters of ABS hydraulic control units and the change rates of brake pressure are obtained, and from which the relationship curves between control signals and the physical characteristics of high-speed switching valve are also obtained. .. Xiaohan, L. et al. [12] established a joint simulation model of pneumatic ABS for commercial vehicles based on AMESim and Simulink software (MathWorks.Inc, Natick, MA, USA), and simulated four typical failure modes of pneumatic ABS to analyze the effects of different failure modes on the braking capacity.

Article Title: Development of Torque Vectoring Control Algorithm for Front Wheel Driven Dual Motor System and Evaluation of Vehicle Dynamics Performance
Article Snippet: This study developed a control algorithm of torque vectoring system to improve the handling performance of a green-car and evaluate the performance of vehicle dynamics to improve the controllability and stability.. Firstly, this study configured the control algorithm with the supervisory controller that decides the control mode by checking the current driving status of a vehicle, target yawrate calculator that reflects the steady-state and transient-state response characteristics according to the control mode, as well as the reference yawrate calculation, desired yaw moment calculation and transferred torque calculation.. The control mode consists of the agile mode that controls the torque vectoring to improve the controllability and the safe mode that controls the torque vectoring to improve stability.

Battery:

Article Title: A combined robust approach based on auto‐regressive long short‐term memory network and moving horizon estimation for state‐of‐charge estimation of lithium‐ion batteries
Article Snippet: Funding information National Natural Science Foundation of China, Grant/Award Numbers: 51375046, 52002025; the National Key Research and Development Program of China under Grant, Grant/Award Number: 2017YFB0102602 Summary State-of-charge (SOC) of battery is one of the important evaluation indexes for the battery management system (BMS) application and driving range estimation of electric vehicles.. However, acquiring accurate battery SOC information is subject to the indeterminacy of initial SOC value, as well as uncertainties and inconsistencies of the battery pack.. To deal with those problems, a combined method based on the auto-regressive long short-term memory network (ARLSTM) and moving horizon estimation (MHE) is put forward.

Construct:

Article Title: A combined robust approach based on auto‐regressive long short‐term memory network and moving horizon estimation for state‐of‐charge estimation of lithium‐ion batteries
Article Snippet: Funding information National Natural Science Foundation of China, Grant/Award Numbers: 51375046, 52002025; the National Key Research and Development Program of China under Grant, Grant/Award Number: 2017YFB0102602 Summary State-of-charge (SOC) of battery is one of the important evaluation indexes for the battery management system (BMS) application and driving range estimation of electric vehicles.. However, acquiring accurate battery SOC information is subject to the indeterminacy of initial SOC value, as well as uncertainties and inconsistencies of the battery pack.. To deal with those problems, a combined method based on the auto-regressive long short-term memory network (ARLSTM) and moving horizon estimation (MHE) is put forward.

Article Title: A Novel Method for Idle-Stop-Start Control of Micro Hybrid Construction Equipment—Part B: A Real-Time Comparative Study
Article Snippet: .. From the results in [12], the powertrain model can be constructed using the advanced co-simulation tool—AMESim (Siemens, Austin, TX, USA) and Simulink of MATLAB. .. This model is the combinati of sub-models in which the sub-models of ICE, star er, pinion-ring gear and belt transmissions, external lo ds, nd ECU are built in AMESim while the sub-models of battery, alternator and electrical load are built in Simulink using Simscape.

Software:

Article Title: A combined robust approach based on auto‐regressive long short‐term memory network and moving horizon estimation for state‐of‐charge estimation of lithium‐ion batteries
Article Snippet: Funding information National Natural Science Foundation of China, Grant/Award Numbers: 51375046, 52002025; the National Key Research and Development Program of China under Grant, Grant/Award Number: 2017YFB0102602 Summary State-of-charge (SOC) of battery is one of the important evaluation indexes for the battery management system (BMS) application and driving range estimation of electric vehicles.. However, acquiring accurate battery SOC information is subject to the indeterminacy of initial SOC value, as well as uncertainties and inconsistencies of the battery pack.. To deal with those problems, a combined method based on the auto-regressive long short-term memory network (ARLSTM) and moving horizon estimation (MHE) is put forward.

Article Title: Experimental assessment of a linear actuator driven by magnetorheological clutches for automotive active suspensions
Article Snippet: .. A set of relevant design requirements for an active suspension actuator for force, linear speed, bandwidth, intrinsic parasitic forces as well as relevant wheel load cases are established with a vehicle in-depth dynamic simulation within Siemens LMS Amesim Imagine Lab software (Amesim) and from on-car accelerometer measurements. ..

Article Title: Developing high-precision battery electric forklift driving cycle with variable cargo weight
Article Snippet: Driving cycles are essential for assessing vehicle energy demand, estimating driving range, and evaluating environmental impacts.. Numerous driving cycles have been developed for passenger cars and buses.. However, tailored driving cycles for logistics vehicles, especially forklifts, remains limited.

Suspension:

Article Title: Experimental assessment of a linear actuator driven by magnetorheological clutches for automotive active suspensions
Article Snippet: .. A set of relevant design requirements for an active suspension actuator for force, linear speed, bandwidth, intrinsic parasitic forces as well as relevant wheel load cases are established with a vehicle in-depth dynamic simulation within Siemens LMS Amesim Imagine Lab software (Amesim) and from on-car accelerometer measurements. ..

other:

Article Title: Development and preliminary verification of a transient analysis code PANES-Tran for Nuclear thermal propulsion
Article Snippet: The Nuclear Thermal Propulsion (NTP) boasts advantages such as high specific impulse, substantial thrust, and extended operating time, giving it a clear edge in deep space exploration and orbital maneuvers.. To fully harness the potential of NTP, transient analysis is crucial to ensure reliability, safety, and performance under various operational conditions.. In this paper, a transient version of NTP analysis code PANES-Tran (Program for Analyzing Nuclear Engine Systems − Transient) was developed for the 110kN expander cycle particle bed reactor (PBR) nuclear thermal propulsion (NTP) system.



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