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Real-Time Embedded Models for Simulation and Control of Clean and Fuel-Efficient Heavy-Duty Diesel Engines

University of Michigan-Saravanan Duraiarasan, Rasoul Salehi, Fucong Wang, Anna Stefanopoulou
Daimler Trucks North America-Marc Allain, Siddharth Mahesh
  • Technical Paper
  • 2020-01-0257
To be published on 2020-04-14 by SAE International in United States
The ever increasing demand for fuel economy and stringent emission norms drives researchers to continuously innovate and improve engine modes to implement adaptive algorithms, where the engine states are continuously monitored and the control variables are manipulated to operate the engine at the most efficient regime. This paper presents a virtual engine developed by modeling a modern diesel engine and aftertreatment which can be used in real-time on a control unit to predict critical diesel engine variables such as fuel consumption and feed gas conditions including emissions, flow and temperature. A physics-based approach is followed in order to capture vital transient airpath and emission dynamics encountered during real driving condition. A minimal realization of the airpath model is coupled with a cycle averaged NOx emissions predictor to estimate transient feed gas NOx during steady state and transient conditions. The complete airpath and NOx emission model was implemented on a rapid prototyping controller and experimentally validated over steady state and transient emission cycles. The overall performance of the reduced order model was comparable to that of…
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Evaluating the Performance of a Conventional and Hybrid Bus operating on Diesel and B20 Fuel for Emissions and Fuel Economy

University of Michigan-Rinav Pillai, Andre Boehman
US Environmental Protection Agency-Matthew Brusstar, Scott Ludlam
  • Technical Paper
  • 2020-01-1351
To be published on 2020-04-14 by SAE International in United States
With ongoing concerns about the elevated levels of ambient air pollution in urban areas and the contribution from heavy-duty diesel vehicles, hybrid electric buses are considered as a potential solution as they are perceived to be less polluting and more fuel-efficient than their conventional engine counterparts. However, recent studies have shown that real-world emissions may be substantially higher than those measured in the laboratory, mainly due to operating conditions that are not fully accounted for in dynamometer test cycles. At the U.S. EPA National Fuel and Vehicle Emissions Laboratory (NVFEL), the in-use criteria emissions and energy efficiency of heavy-duty class 8 vehicles (up to 80,000 lbs) may be evaluated under controlled conditions in the heavy-duty chassis dynamometer test. The present study evaluated the performance of a conventional bus and hybrid bus for emissions and fuel economy under representative test cycles (including cold start and hot start conditions) with Diesel (#2) and Biodiesel (B20) fuel. The conventional bus was equipped with a Cummins ISL 8.3L engine and a Diesel Particulate Filter (DPF) and Diesel Oxidation Catalyst…
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Accelerometer-Based Estimation of Combustion Features for Engine Feedback Control

University of Michigan-Bryan Maldonado, Anna Stefanopoulou
Army Research Laboratory-Kenneth Kim
  • Technical Paper
  • 2020-01-1147
To be published on 2020-04-14 by SAE International in United States
An experimental investigation of non-intrusive combustion sensing was performed using a tri-axial accelerometer mounted to a small-bore high-speed 4-cylinder diesel engine. This study investigates potential techniques to extract combustion features from accelerometer signals to be used for cycle-to-cycle engine control. Selection of accelerometer location and vibration axis were performed by analyzing vibration signals for three different locations along the block for all three of the accelerometer axes. A magnitude squared coherence (MSC) statistical analysis was used to select the best location and axis. Based on previous work from the literature, the vibration signal filtering was optimized and the filtered vibration signals were analyzed. It was found that the vibration signals correlate well with the second derivative of pressure during the initial stages of combustion. Two combustion parameters were the focus of this investigation, start of combustion (SOC) and crank angle of fifty-percent heat release (CA50). The results showed that, for a wide range of engine conditions, SOC can be obtained solely from the first derivative of the vibration signal with respect to crank angle. In…
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Minimization of Electric Heating of the Traction Induction Machine Rotor

University of Michigan-Sergey Gladyshev
South Ural State University-Elena Nikiforova, Victor Smolin
  • Technical Paper
  • 2020-01-0562
To be published on 2020-04-14 by SAE International in United States
The article solves the problem of reducing electric power losses of the traction induction machine rotor to prevent its overheating in nominal and high-load modes. Electric losses of the rotor power are optimized by the stabilization of the main magnetic flow of the electric machine at a nominal level with the amplitude-frequency control in a wide range of speeds and increased loads. The quasi-independent excitation of the induction machine allows us to increase the rigidity of mechanical characteristics, decrease the rotor slip at nominal loads and overloads and significantly decrease electrical losses in the rotor as compared to other control methods. The article considers the technology of converting the power of individual phases into a single energy flow using a three-phase electric machine equivalent circuit and obtaining an energy model in the form of equations of instantaneous active and reactive power balance. The quasi-independent excitation of the induction machine is performed according to the model by stabilizing the current of the magnetizing branch using the algorithms to control the voltage amplitude, synchronous frequency and electromagnetic…
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Innovative additive manufacturing process for successful production of 7000 series aluminum alloy components using Smart Optical Monitoring System

University of Michigan-Jyoti Mazumder
SenSigma LLC-Jay Choi, Alex Rice
  • Technical Paper
  • 2020-01-1300
To be published on 2020-04-14 by SAE International in United States
Aircraft components are commonly produced with 7000 series aluminum alloys due to its weight, strength, and fatigue properties. Auto Industry is also choosing more and more aluminum component for weight reduction. Current additive manufacturing (AM) methods fall short of successfully producing 7000 series aluminum alloys due to the reflective nature of the material along with elements with low vaporization temperature. Moreover, lacking in ideal thermal control, print inherently defective products with such issues as poor surface finish alloying element loss and porosity. All these defects contribute to reduction of mechanical strength. By monitoring plasma with spectroscopic sensors, multiple information such as line intensity, standard deviation, plasma temperature or electron density, and by using different signal processing algorithm such as vector machine training or wavelet transforming, AM defects have been detected and classified. For composition analysis, the ratio of the maximum intensities of Mg(I)/Al(I) shows a strong trend with the amount of Zn and Mg in the powder, and the results are extremely promising regarding the ability to use the online spectra for real time determination…
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Energy, Fuels, and Cost Analyses for the M1A2 Tank: A Weight Reduction Case Study

University of Michigan-Geoffrey M. Lewis, Gregory A. Keoleian
CCDC Ground Vehicle Systems Center-Rob Hart
  • Technical Paper
  • 2020-01-0173
To be published on 2020-04-14 by SAE International in United States
Reducing the weight of the Abrams M1A2 tank has been studied by lightweighting three separate components: hull, suspension, and track, resulting in 5.1, 1.3, and 0.6 percent tank mass reductions, respectively. The impact of replacing an existing with a lightweight component on tank performance are evaluated in terms of three metrics: primary energy demand (PED), cost, and tank operational fuel consumption (FC). The life cycle phases included are: preproduction, material production, part fabrication, and tank operation. The metrics for each of the tank lightweight components are expressed as ratios: for example, the sum of PED for the four life cycle phases of the lightweight tank / the PED for the operational phase only of the base case (unmodified) tank. For Army defined duty cycles, a FC/mass elasticity of 0.55 was employed for estimating changes in tank FC upon mass reductions. On a per tank basis, we find that the relative costs to retrofit and operate a tank with a lightweight hull ranges from 19 to 3.5 times those for simply operating (fuel costs) an existing…
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Machine Learning Techniques for the Prediction of Combustion Events in Cooperative Fuel research Engine (CFR) at Homogeneous Charge Compression Ignition (HCCI) conditions.

University of Michigan-Kwang Hee Yoo, Andre Boehman
Aramco Services Co.-Alexander Voice
  • Technical Paper
  • 2020-01-1132
To be published on 2020-04-14 by SAE International in United States
This research assesses the capability of data-science models to predict the combustion events occurring for certain input conditions in Cooperative Fuel Research Engine (CFR) at Homogeneous Charge Compression Ignition (HCCI) conditions. The experimental data from CFR engine of University of Michigan (UM), operated at different input conditions for various gasoline type fuels was utilized for the study. The current study developed a capable machine learning framework to predict the auto-ignition propensity of a fuel under HCCI conditions. The combustion events happening at HCCI conditions in CFR engine are primarily classified into four different classes depending on the combustion phasing and pressure rise during the combustion in engine. The classes are: no ignition, normal combustion, high MPRR and early CA 50. Two machine learning (ML) models, K-nearest neighbors and Support Vector Machines, are compared for their classification capabilities of combustion events. Seven conditions are used as the input features for this ML models viz. Research Octane Number (RON) of fuel, Sensitivity of fuel (S), fuel rate (J/L/cycle), oxygen mole fraction, intake temperature and pressure, and compression…
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Numerical Investigation of Friction Material Contact Mechanics in Automotive Clutches

University of Michigan-Nikolaos Katopodes
FCC Co., Ltd.-Masatoshi Miyagawa, Takahiro Tsuchiya, Shinji Nakamura, Matthew Wendel
  • Technical Paper
  • 2020-01-1417
To be published on 2020-04-14 by SAE International in United States
A wet clutch model is required in automotive propulsion system simulations for enabling robust design and control development. It commonly assumes a Coulomb’s model for simplicity, even though it does not physically represent viscous torque transfer. A Coulomb friction coefficient is treated as a tuning parameter in simulations to match vehicle data for targeted conditions. The simulations tend to deviate from actual behaviors for different drive conditions unless the friction coefficient is adjusted repeatedly. Alternatively, a complex hydrodynamic model, coupled with a surface contact model, is utilized to enhance the fidelity of system simulations for broader conditions. The theory of elastic asperity deformation is conventionally employed to model clutch surface contact. However, the recent examination of friction material shows that elasticity modulus of surface fibers significantly exceeds contact load, implying no deformation of fibers. This article investigates the friction material contact mechanics through numerical simulations. A surface model is constructed based on microscopic examination of material topography and properties. FEM simulation is conducted to examine the interactions between surface fibers and surrounding medium under loaded…
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The Effect of EGR Dilution on the Heat Release Rates of Boosted Spark-Assisted Compression Ignition (SACI) Engines

University of Michigan-Vassilis Triantopoulos, Stanislav Bohac, Jason Martz, George Lavoie, Andre Boehman
Robert Bosch LLC-Jeff Sterniak
  • Technical Paper
  • 2020-01-1134
To be published on 2020-04-14 by SAE International in United States
This paper presents an experimental investigation of the impact of EGR dilution on the tradeoff between flame and end-gas autoignition heat release in a Spark-Assisted Compression Ignition (SACI) combustion engine. The mixture was maintained stoichiometric and fuel-to-charge equivalence ratio (ϕ') was controlled by varying the EGR dilution level at constant engine speed. Under all conditions investigated, end-gas autoignition timing was maintained constant by modulating the mixture temperature and spark timing. Experiments at constant intake pressure and spark timing showed that as ϕ' is increased, lower mixture temperatures are needed to match end-gas autoignition timing. Higher ϕ' mixtures exhibited faster initial flame burn rates, which were attributed to the higher estimated laminar flame speeds immediately after spark timing. At constant intake pressure and mass fraction burned at the onset of autoignition, end-gas autoignition rates increased significantly at higher ϕ' conditions. The increasing trends in peak autoignition rate and end-gas energy at autoignition onset were found to be consistent for all intake pressures ranging from 80 kPa to 150 kPa. For a constant spark timing, the mass…
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Engine and Aftertreatment Co-Optimization of Connected HEVs via Multi-Range Vehicle Speed Planning and Prediction

University of Michigan-Qiuhao Hu, Mohammad R. Amini, Yiheng Feng, Zhen Yang, Hao Wang, Ilya Kolmanovsky, Jing Sun
Ford Motor Company-Ashley Wiese, Zeng Qiu, Julia Buckland
  • Technical Paper
  • 2020-01-0590
To be published on 2020-04-14 by SAE International in United States
Connected vehicles (CVs) have situational awareness that can be exploited for control and optimization of the powertrain system. While extensive studies have been carried out for energy efficiency improvement of CVs via eco-driving and platooning, the implication of such technologies on the thermal responses of CVs (including those of the engine and aftertreatment systems) has not been fully investigated. One of the key challenges in leveraging connectivity for optimization-based thermal management of CVs is the relatively slow thermal dynamics, which necessitate the use of a long prediction horizon to achieve the best performance. Long-term prediction of the CV speed, unlike the short-range prediction based on vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communications-based information, is difficult and error-prone. The multiple timescales inherent to power and thermal systems call for a variable timescale optimization framework with access to short- and long-term vehicle speed preview. To this end, a model predictive controller (MPC) with a multi-range speed preview for integrated power and thermal management (iPTM) of connected hybrid electric vehicles (HEVs) is presented in this paper. The MPC is…