scholarly journals Electro-Thermal Model-Based Design of Bidirectional On-Board Chargers in Hybrid and Full Electric Vehicles

Electronics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 112
Author(s):  
Pierpaolo Dini ◽  
Sergio Saponara
Keyword(s):  
Thermal Behaviour ◽  
Waiting Times ◽  
Robustness Analysis ◽  
Practical Interest ◽  
Operating Conditions ◽  
Control Loops ◽  
Model Based ◽  
Dual Active Bridge ◽  
Pole Type ◽  
Switching Devices

In this paper, a model-based approach for the design of a bidirectional onboard charger (OBC) device for modern hybrid and fully electrified vehicles is proposed. The main objective and contribution of our study is to incorporate in the same simulation environment both modelling of electrical and thermal behaviour of switching devices. This is because most (if not all) of the studies in the literature present analyses of thermal behaviour based on the use of FEM (Finite Element Method) SWs, which in fact require the definition of complicated models based on partial derivative equations. The simulation of such accurate models is computationally expensive and, therefore, cannot be incorporated into the same virtual environment in which the circuit equations are solved. This requires long waiting times and also means that electrical and thermal models do not interact with each other, limiting the completeness of the analysis in the design phase. As a case study, we take as reference the architecture of a modular bidirectional single-phase OBC, consisting of a Totem Pole-type AC/DC converter with Power Factor Correction (PFC) followed by a Dual Active Bridge (DAB) type DC/DC converter. Specifically, we consider a 7 kW OBC, for which its modules consist of switching devices made with modern 900 V GaN (Gallium Nitrade) and 1200 V SiC (Silicon Carbide) technologies, to achieve maximum performance and efficiency. We present a procedure for sizing and selecting electronic devices based on the analysis of behaviour through circuit models of the Totem Pole PFC and DAB converter in order to perform validation by using simulations that are as realistic as possible. The developed models are tested under various operating conditions of practical interest in order to validate the robustness of the implemented control algorithms under varying operating conditions. The validation of the models and control loops is also enhanced by an exhaustive robustness analysis of the parametric variations of the model with respect to the nominal case. All simulations obtained respect the operating limits of the selected devices and components, for which its characteristics are reported in data sheets both in terms of electrical and thermal behaviour.

Blind Identification of Impact Forces From Multiple Remote Vibratory Measurements

2000 ◽  
Author(s):  
J. Antunes ◽  
P. Izquierdo ◽  
M. Paulino
Keyword(s):  
Explicit Knowledge ◽  
Transfer Functions ◽  
Dynamical Behavior ◽  
Practical Interest ◽  
Operating Conditions ◽  
Blind Identification ◽  
Minimum Entropy ◽  
Response Measurement ◽  
Identification Techniques ◽  
The Impact

Abstract Structures and mechanical components are often subjected to impulsive forces. There is a need for identification techniques which enable monitoring of such loads under operating conditions. For safety reasons and convenience, force identification must often be based on response motions sensed at accessible locations, remote from the impact points. In our previous work we presented techniques for the experimental identification of both isolated impacts and complex rattling forces on a beam, generated at a single and also at several impacting supports. The system dynamical behavior was modeled using traveling flexural beam waves. Although successful, these techniques obviously assume a good understanding of the system dynamic parameters. This is not always the case, a fact that highlights the practical interest of blind identification techniques. This relatively recent field, connected with higher-order statistics, avoids any explicit knowledge of the system transfer functions or impulse responses. Our previous work, based on a single response measurement, is extended in this paper to include several simultaneous responses. We develop a multi-trace version of Wiggins minimum-entropy blind deconvolution algorithm. From numerical simulations and experiments, it is shown that the robustness to noise contamination is increased by using multiple response data. These results suggest that blind identification techniques will prove very useful in practical situations.

Study On Automatic Adaptation for Control-Oriented Model of Advanced Diesel Engine

2021 ◽  
Author(s):  
Shunki Nishii ◽  
Yudai Yamasaki
Keyword(s):  
Operating Conditions ◽  
Physical Models ◽  
Model Parameters ◽  
Training Methods ◽  
Model Based Control ◽  
Practical Applications ◽  
Model Based ◽  
Automatic Adaptation ◽  
Automobile Engines ◽  
Adaptation Method

Abstract To achieve high thermal efficiency and low emission in automobile engines, advanced combustion technologies using compression autoignition of premixtures have been studied, and model-based control has attracted attention for their practical applications. Although simplified physical models have been developed for model-based control, appropriate values for their model parameters vary depending on the operating conditions, the engine driving environment, and the engine aging. Herein, we studied an onboard adaptation method of model parameters in a heat release rate (HRR) model. This method adapts the model parameters using neural networks (NNs) considering the operating conditions and can respond to the driving environment and the engine aging by training the NNs onboard. Detailed studies were conducted regarding the training methods. Furthermore, the effectiveness of this adaptation method was confirmed by evaluating the prediction accuracy of the HRR model and model-based control experiments.

Roboterbasierte spanende Bearbeitung*/Robot-Based Milling Operation. Machine Learning Algorithm for a model-based feed-forward torque control

2019 ◽  
Vol 109 (05) ◽  
pp. 352-357
Author(s):  
C. Brecher ◽  
L. Gründel ◽  
L. Lienenlüke ◽  
S. Storms
Keyword(s):  
Machine Learning ◽  
Position Control ◽  
Learning Algorithm ◽  
Milling Process ◽  
Industrial Robots ◽  
Torque Control ◽  
Feed Forward ◽  
Control Loops ◽  
Model Based ◽  
Machine Learning Approach

Die Lageregelung von konventionellen Industrierobotern ist nicht auf den dynamischen Fräsprozess ausgelegt. Eine Möglichkeit, das Verhalten der Regelkreise zu optimieren, ist eine modellbasierte Momentenvorsteuerung, welche in dieser Arbeit aufgrund vieler Vorteile durch einen Machine-Learning-Ansatz erweitert wird. Hierzu wird die Umsetzung in Matlab und die simulative Evaluation erläutert, die im Anschluss das Potenzial dieses Konzeptes bestätigt.   The position control of conventional industrial robots is not designed for the dynamic milling process. One possibility to optimize the behavior of the control loops is a model-based feed-forward torque control which is supported by a machine learning approach due to many advantages. The implementation in Matlab and the simulative evaluation are explained, which subsequently confirms the potential of this concept.

scholarly journals Heuristic study of a full can implementation on a network of digital controllers based on experimental data

2020 ◽  
pp. 17-23
Author(s):  
Carlos Alberto Luján-Ramírez ◽  
Jesús Sandoval-Gío ◽  
Agustín Alfonso Flores-Novelo ◽  
Juan Alberto Ojeda-Arana
Keyword(s):  
Experimental Data ◽  
Parametric Identification ◽  
Operating Conditions ◽  
Access Time ◽  
Area Network ◽  
Digital Controllers ◽  
Electromagnetic Brake ◽  
Control Loops ◽  
Heuristic Study ◽  
Exchange Data

Over time, the CAN (Controller Area Network) communication bus has been implemented in different technological sectors, within which, depending on the application, the bus implementation may change. On the other hand, the design and implementation of digital controls based on experimental data is a well-known topic in the automation industry where the acquisition system is of great importance. In this document, a heuristic study of the behavior of a Full CAN network is reported to implement digital controllers in two interconnected control loops. This study takes into account the access time to the bus and the amount of data sent when observing the response to disturbances. The design of two digital controllers is presented based on the parametric identification of two plants: a DC motor with an electromagnetic brake and a pneumatic levitator. Using PSoC® microcontrollers, a Full CAN network is implemented, where the digital controllers exchange data by randomly accessing the bus. A specially designed interface allows visualizing the speed and amount of data transferred under different operating conditions of the control loops. At the document end, the experimental data obtained are discussed.

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