Eddy Current Brake Control for Test Cycles Simulation

Author(s):  
Enrico Corti

On-vehicle (rolls dynamometer or road) tests are usually more expensive and time-consuming than test bench ones. Furthermore, sometimes results would be useful during vehicles design phase. The paper aim is to present a methodology that allows simulating the vehicle on an engine test cell, by properly controlling the bench actuators. Engine operating conditions mainly depend on speed and load, which are determined by the vehicle driving conditions: the speed-time trend assigned for the vehicle must be converted into equivalent speed-time and load-time trends for the engine, and used for feedback control of brake and accelerator actuators. To evaluate the engine load torque it is necessary to know vehicle characteristics (mass, gear ratios, wheels radius, drag coefficient, frontal area, etc.) and driving conditions: the real vehicle can thus be substituted with a virtual vehicle. The methodology has been applied to simulate an ECE-EUDC driving cycle, which is usually carried out on the rolls dynamometer, as imposed by regulations. During such test the vehicle has to follow an assigned speed-time trajectory, while road load and vehicle inertia are simulated and calibrated using a standard procedure. The test is subject to human error, since the driver does not follow exactly the theoretical speed trend, while using robot-drivers increases the setup cost. The same test has been reproduced on a standard engine bench. This setup would be useful to tune the engine correctly and to study the effects of vehicle characteristics variation, thus allowing to determine the correct strategy for emissions reduction, or to estimate the vehicle emission performance, before it is available for chassis dynamometer tests. The same system could be used for real time implementation of control strategies involving both the vehicle and the engine, such as traction control algorithms. Furthermore driving conditions simulations, executed by electronically controlling engine speed and load trajectories, would be more repeatable than human driving on the chassis dynamometer, and their cost would be substantially smaller. The paper shows how the vehicle speed trend can be converted into engine speed and load trends with a physical system model, and then used to control the bench using a real time control system, thus performing a vehicle driving cycle simulation.

2015 ◽  
Vol 161 (2) ◽  
pp. 78-88
Author(s):  
Zdzisław STELMASIAK ◽  
Jerzy LARISCH ◽  
Dariusz PIETRAS

The paper presents the results of investigations performed on a Fiat 1.3 MultiJet engine fueled with natural gas (CNG) and diesel oil. The primary aim was to determine the influence of a small additive of natural gas on the exhaust gas opacity under variable engine operating conditions. The tests were performed for the engine work points n–Mo (engine speed– torque) reproducing the NEDC cycle. The selection of the work points was carried out according to the criterion of greatest share in the NEDC homologation test, covering the entire engine field of work used in the realization of the test on a chassis dynamometer. In the tests, the authors applied different energy shares of natural gas in the range 15–35.6%. The smoke opacity was analyzed in the FSN and mass scales [mg/m3 ]. The results of the investigations may be used in the design of electronic controllers for natural gas engines and in the adaptation engines to CNG fueling.


Author(s):  
Enrico Corti

International emission tests (EPA, SFTP, MVEG-B, J-10.15, etc.) are carried out with vehicles running on the rolls dynamometer. Results, in terms of total emissions, are influenced by vehicles parameters such as mass, gear ratios, front surface, drag coefficient, etc. It would be useful, in the automobiles design phase, to have information about the impact of these parameters on total emissions. The obvious solution would be to build up a complete vehicle model to simulate performance and emission levels. Engine pollutants production modeling is the weak point, since it is difficult to obtain reliable results. Anyway it is possible to avoid pollutants production simulation, testing the actual engine under the same operating condition it would face inside the car’s hood. This paper describes a methodology whose aim is to test the engine on a standard test bench, simulating on-board operating conditions. An equivalence condition has to be satisfied in order to guarantee the methodology effectiveness: engine speed and Manifold Absolute Pressure (MAP) must always match for the two types of test performed on the same driving cycle. Engine speed and torque can be controlled through the bench actuators, their values depending on the simulated vehicle motion: once the car dynamics are simulated by means of a model, engine speed and torque corresponding to the given driving cycle can in fact be evaluated. The model is solved in real time, its output being the brake load torque value satisfying the equivalence condition. The brake controller, used as a slave, regulates the engine operating conditions consequently. The global model incorporates tires, aerodynamic forces, clutch, gearbox and driveline behaviors simulation: its response has been first validated comparing its outputs with data measured on board, and then it has been used to control an eddy current brake, for vehicle test simulation on the test bench. Two different control philosophies can be used: either a human driver or an automatic controller can ride the simulated car. The influence of vehicle parameters and gearshift mode on fuel consumption and pollutant emissions can be investigated.


Author(s):  
Jerald A. Caton

Nitric oxide emissions were estimated for a homogeneous-charge, spark-ignited automotive engine using a cycle simulation which employed three zones for the combustion process: (1) unburned gas, (2) adiabatic core region, and (3) boundary-layer gas. The use of the adiabatic core region has been shown to be especially necessary to capture the production of nitric oxides which are highly temperature dependent. The effects of major engine parameters such as equivalence ratio, spark timing, inlet manifold pressure, and engine speed on nitric oxide emissions are examined. In particular, the detail reasons for the effects of these engine parameters on the nitric oxide emissions are presented. Comparisons are completed between the computed values and a set of published measurements for the nitric oxide concentrations. Although not all engine parameters were known, reasonable agreement is demonstrated for most cases. In particular, the variations of nitric oxide concentrations as engine speed increased were duplicated. As an example, four operating conditions are examined in detail to help explain the measured results. Nitric oxide emissions are shown to be mainly the net result of gas temperatures, oxygen concentrations, and residence times.


2020 ◽  
Vol 13 (2) ◽  
pp. 126-140
Author(s):  
Jing Gan ◽  
Xiaobin Fan ◽  
Zeng Song ◽  
Mingyue Zhang ◽  
Bin Zhao

Background: The power performance of an electric vehicle is the basic parameter. Traditional test equipment, such as the expensive chassis dynamometer, not only increases the cost of testing but also makes it impossible to measure all the performance parameters of an electric vehicle. Objective: A set of convenient, efficient and sensitive power measurement system for electric vehicles is developed to obtain the real-time power changes of hub-motor vehicles under various operating conditions, and the dynamic performance parameters of hub-motor vehicles are obtained through the system. Methods: Firstly, a set of on-board power test system is developed by using virtual instrument (Lab- VIEW). This test system can obtain the power changes of hub-motor vehicles under various operating conditions in real-time and save data in real-time. Then, the driving resistance of hub-motor vehicles is analyzed, and the power performance of hub-motor vehicles is studied in depth. The power testing system is proposed to test the input power of both ends of the driving motor, and the chassis dynamometer is combined to test so that the output efficiency of the driving motor can be easily obtained without disassembly. Finally, this method is used to carry out the road test and obtain the vehicle dynamic performance parameters. Results: The real-time current, voltage and power, maximum power, acceleration time and maximum speed of the vehicle can be obtained accurately by using the power test system in the real road experiment. Conclusion: The maximum power required by the two motors reaches about 9KW, and it takes about 20 seconds to reach the maximum speed. The total power required to maintain the maximum speed is about 7.8kw, and the maximum speed is 62km/h. In this article, various patents have been discussed.


Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4136
Author(s):  
Clemens Gößnitzer ◽  
Shawn Givler

Cycle-to-cycle variations (CCV) in spark-ignited (SI) engines impose performance limitations and in the extreme limit can lead to very strong, potentially damaging cycles. Thus, CCV force sub-optimal engine operating conditions. A deeper understanding of CCV is key to enabling control strategies, improving engine design and reducing the negative impact of CCV on engine operation. This paper presents a new simulation strategy which allows investigation of the impact of individual physical quantities (e.g., flow field or turbulence quantities) on CCV separately. As a first step, multi-cycle unsteady Reynolds-averaged Navier–Stokes (uRANS) computational fluid dynamics (CFD) simulations of a spark-ignited natural gas engine are performed. For each cycle, simulation results just prior to each spark timing are taken. Next, simulation results from different cycles are combined: one quantity, e.g., the flow field, is extracted from a snapshot of one given cycle, and all other quantities are taken from a snapshot from a different cycle. Such a combination yields a new snapshot. With the combined snapshot, the simulation is continued until the end of combustion. The results obtained with combined snapshots show that the velocity field seems to have the highest impact on CCV. Turbulence intensity, quantified by the turbulent kinetic energy and turbulent kinetic energy dissipation rate, has a similar value for all snapshots. Thus, their impact on CCV is small compared to the flow field. This novel methodology is very flexible and allows investigation of the sources of CCV which have been difficult to investigate in the past.


Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1104
Author(s):  
Shin-Yan Chiou ◽  
Kun-Ju Lin ◽  
Ya-Xin Dong

Positron emission tomography (PET) is one of the commonly used scanning techniques. Medical staff manually calculate the estimated scan time for each PET device. However, the number of PET scanning devices is small, the number of patients is large, and there are many changes including rescanning requirements, which makes it very error-prone, puts pressure on staff, and causes trouble for patients and their families. Although previous studies proposed algorithms for specific inspections, there is currently no research on improving the PET process. This paper proposes a real-time automatic scheduling and control system for PET patients with wearable sensors. The system can automatically schedule, estimate and instantly update the time of various tasks, and automatically allocate beds and announce schedule information in real time. We implemented this system, collected time data of 200 actual patients, and put these data into the implementation program for simulation and comparison. The average time difference between manual and automatic scheduling was 7.32 min, and it could reduce the average examination time of 82% of patients by 6.14 ± 4.61 min. This convinces us the system is correct and can improve time efficiency, while avoiding human error and staff pressure, and avoiding trouble for patients and their families.


2015 ◽  
Author(s):  
Gopal Athani ◽  
Srinivasa Raju Gavarraju ◽  
Shashi Kulkarni ◽  
Ramakrishna Koduru ◽  
Kapil Dongare ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
pp. 377
Author(s):  
Michele Scarpiniti ◽  
Enzo Baccarelli ◽  
Alireza Momenzadeh ◽  
Sima Sarv Ahrabi

The recent introduction of the so-called Conditional Neural Networks (CDNNs) with multiple early exits, executed atop virtualized multi-tier Fog platforms, makes feasible the real-time and energy-efficient execution of analytics required by future Internet applications. However, until now, toolkits for the evaluation of energy-vs.-delay performance of the inference phase of CDNNs executed on such platforms, have not been available. Motivated by these considerations, in this contribution, we present DeepFogSim. It is a MATLAB-supported software toolbox aiming at testing the performance of virtualized technological platforms for the real-time distributed execution of the inference phase of CDNNs with early exits under IoT realms. The main peculiar features of the proposed DeepFogSim toolbox are that: (i) it allows the joint dynamic energy-aware optimization of the Fog-hosted computing-networking resources under hard constraints on the tolerated inference delays; (ii) it allows the repeatable and customizable simulation of the resulting energy-delay performance of the overall Fog execution platform; (iii) it allows the dynamic tracking of the performed resource allocation under time-varying operating conditions and/or failure events; and (iv) it is equipped with a user-friendly Graphic User Interface (GUI) that supports a number of graphic formats for data rendering. Some numerical results give evidence for about the actual capabilities of the proposed DeepFogSim toolbox.


1992 ◽  
Vol 3 (2) ◽  
pp. 176-192
Author(s):  
T.W. Abou-Arab ◽  
M. Othman ◽  
Y.S.H. Najjar

Increasing requirements for vehicle confort, economy and reliability lead some investigators to consider the relationships between the mechanical vibrations with the heat and fluid flow induced vibration and noise in a more accurate manner. This paper describes the variation of the vibration phenomena associated with the motion of some engine components under different operating conditions. The measured vibration spectra indicates its capability in predicting symptoms of early engine failures, hence, expediting their control using a suitable feedback system. Parametric studies involving the effect of air-fuel ratio, ignition timing and engine speed on the vibration pattern are also carried out. These studies indicate that the amplitude of vibration decreases as the speed increases then increases again after certain engine speed. The effect of ignition system characteristic on the induced vibration are obtained and the correlation between the developed power and the engine dynamics over a range of operating conditions are discussed.


Author(s):  
Geoffrey Momin ◽  
Raj Panchal ◽  
Daniel Liu ◽  
Sharman Perera

Human error accounts for about 60% of the annual power loss due to maintenance incidents in the fossil power industry. The International Atomic Energy Agency reports that 80\% of industrial accidents in the nuclear industry can be attributed to human error and 20\% to equipment failure. The Personal Augmented Reality Reference System (PARRS) is a suite of computer-mediated reality applications that looks to minimize human error by digitizing manual procedures and providing real-time monitoring of hazards present in an environment. Our mission is to be able to provide critical feedback to inform personnel in real-time and protect them from avoidable hazards. PARRS aims to minimize human error and increase worker productivity by bringing innovation to safety and procedural compliance by leveraging technologies such as augmented reality, LiDAR, computer machine learning and particulate mapping using remote systems.


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