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Torque and Pressure CFD Correlation of a Torque Converter

SAE International Journal of Passenger Cars - Mechanical Systems

Ford Motor Company, USA-Steve Frait, Ram Devendran
Michigan Technological University, USA-Edward De Jesus Rivera, Mark Woodland, Darrell Robinette, Jason Blough, Carl Anderson
  • Journal Article
  • 06-12-03-0012
Published 2019-08-22 by SAE International in United States
A torque converter was instrumented with 29 pressure transducers inside five cavities under study (impeller, turbine, stator, clutch cavity between the pressure plate and the turbine shell). A computer model was created to establish correlation with measured torque and pressure. Torque errors between test and simulation were within 5% and K-Factor and torque ratio errors within 2%. Turbulence intensity on the computer model was used to simulate test conditions representing transmission low and high line pressure settings. When turbulence intensity was set to 5%, pressure simulation root mean square errors were within 11%-15% for the high line pressure setting and up to 34% for low line pressure setting. When turbulence intensity was increased to 50% for the low line pressure settings, a 6% reduced root mean square error in the pressure simulations was seen. For all pressure settings, cavities closer to the converter inlet required a 5% turbulence intensity while the cavities inside or near the torus were better suited with 50% turbulence intensity levels.
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The Utilization of Onboard Sensor Measurements for Estimating Driveline Damping

Michigan Technological University-Jon Furlich, Jason Blough, Darrell Robinette
Published 2019-06-05 by SAE International in United States
The proliferation of small silicon micro-chips has led to a large assortment of low-cost transducers for data acquisition. Production vehicles on average exploit more than 60 on board sensors, and that number is projected to increase beyond 200 per vehicle by 2020. Such a large increase in sensors is leading the fourth industrial revolution of connectivity and autonomy. One major downfall to installing many sensors is compromises in their accuracy and processing power due to cost limitations for high volume production. The same common errors in data acquisition such as sampling, quantization, and multiplexing on the CAN bus must be accounted for when utilizing an entire array of vehicle sensors. A huge advantage of onboard sensors is the ability to calculate vehicle parameters during a daily drive cycle to update ECU calibration factors in real time. One such parameter is driveline damping, which changes with gear state and drive mode. A damping value is desired for every gear state. Recent years have seen an increasing number of forward gear ratios, from 8-10 in production vehicles.…
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Testing Methods and Signal Processing Strategies for Automatic Transmission Transient Multiplexed Pressure Data

Ford Motor Company-Steve Frait, Ram Sudarsan Devendran
Michigan Technological University-Mark Woodland, Jason Blough, Darrell Robinette, Carl Anderson
Published 2019-06-05 by SAE International in United States
Transmissions have multiple transient events that occur from gear shifting to torque converter clutch application. These transients can be difficult to capture and observe. A six speed front wheeled drive transmission was instrumented with pressure transducers to measure clutches and the torque converter. Due to size restrictions internal to the torque converter the data had to be multiplexed across three different transmitters. A method to capture a transient event through the use of multiplexed data was developed to create a data set with the transient event occurring on each channel. Once testing is completed, the data has to be split into individual channels and synced with the operational data. The data then can be used in both time and frequency domain analysis. It is important to understand that the data is not continuous and must be taken into consideration when post processing it for further results.
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Methods of Pegging Cylinder Pressure to Maximize Data Quality

Michigan Tech APS LABS-Jeremy Worm
Michigan Technological Univ-Darrell Robinette
Published 2019-04-02 by SAE International in United States
Engine cylinder pressure is traditionally measured with a piezo-electric pressure transducer, and as such, must be referenced or pegged to a known value. Frequently, the cylinder pressure is pegged to the pressure in the intake manifold plenum whereby the manifold absolute pressure (MAP) at the end of the intake stroke is measured and the cylinder pressure trace for the entire cycle is adjusted such that the cylinder pressure is set equal to the manifold pressure at the end of the intake stroke. However, any error in pegging induces an error in the cylinder pressure trace, which has an adverse effect on the entire combustion analysis. This research is focused on assessing the pegging error for several pegging methods across a wide range of engine operating conditions, and ultimately determining best practices to minimize error in pegging and the calculated combustion metrics. The study was conducted through 1D simulations using the commercially available GT-Power. The test matrix included variations of speed, load, intake runner length and intake valve timing. Five different pegging locations were compared, and…
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PHEV Real World Driving Cycle Energy and Fuel and Consumption Reduction Potential for Connected and Automated Vehicles

Michigan Technological University-Darrell Robinette, Eric Kostreva, Alexandra Krisztian, Anthony Lackey, Christopher Morgan, Joshua Orlando, Neeraj Rama
Published 2019-04-02 by SAE International in United States
This paper presents real-world driving energy and fuel consumption results for the second-generation Chevrolet Volt plug-in hybrid electric vehicle (PHEV). A drive cycle, local to Michigan Technological University, was designed to mimic urban and highway driving test cycles in terms of distance, transients and average velocity, but with significant elevation changes to establish an energy intensive real-world driving cycle for assessing potential energy savings for connected and automated vehicle (CAV) control. The investigation began by establishing baseline and repeatability of energy consumption at various battery states of charge. It was determined that drive cycle energy consumption under a randomized set of boundary conditions varied within 3.6% of mean energy consumption regardless of initial battery state of charge. After completing 30 baseline drive cycles, a design for six sigma (DFSS) L18 array was designed to look at sensitivity of a range of parameters to energy consumption as related to connected and automated vehicles to target highest return on engineering development effort. The parameters explored in the DFSS array that showed the most sensitivity, in order of…
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Control-Oriented Modeling of a Vehicle Drivetrain for Shuffle and Clunk Mitigation

Ford Research & Advanced Engineering-Maruthi Ravichandran, Mary Farmer, Jeff Doering
Michigan Technological University-Prithvi Reddy, Kaushal Darokar, Darrell Robinette, Mahdi Shahbakhti, Jason Blough
Published 2019-04-02 by SAE International in United States
Flexibility and backlash of vehicle drivelines typically cause unwanted oscillations and noise, known as shuffle and clunk, during tip-in and tip-out events. Computationally efficient and accurate driveline models are necessary for the design and evaluation of torque shaping strategies to mitigate this shuffle and clunk. To accomplish these goals, this paper develops a full-order physics-based model and uses this model to develop a reduced-order model (ROM), which captures the main dynamics that influence the shuffle and clunk phenomena. The full-order model (FOM) comprises several components, including the engine as a torque generator, backlash elements as discontinuities, and propeller and axle shafts as compliant elements. This model is experimentally validated using the data collected from a Ford vehicle. The validation results indicate less than 1% error between the model and measured shuffle oscillation frequencies. The reduced-order model is derived by lumping 24 inertia elements into 2 elements, 3 stiffness and damping elements into 2 elements, and 2 backlashes into 1 element. As part of the reduced-order model development, the paper (i) investigates the effect of using…
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Route-Optimized Energy Management of Connected and Automated Multi-Mode Plug-In Hybrid Electric Vehicle Using Dynamic Programming

Michigan Technological University-Neeraj Rama, Huanqing Wang, Joshua Orlando, Darrell Robinette, Bo Chen
Published 2019-04-02 by SAE International in United States
This paper presents a methodology to optimize the blending of charge-depleting (CD) and charge-sustaining (CS) modes in a multi-mode plug-in hybrid electric vehicle (PHEV) that reduces overall energy consumption when the selected route cannot be completely driven in all-electric mode. The PHEV used in this investigation is the second-generation Chevrolet Volt and as many as four instrumented vehicles were utilized simultaneously on road to acquire validation data. The optimization method used is dynamic programming (DP) paired with a reduced-order powertrain model to enable onboard embedded controller compatibility and computational efficiency in optimally blending CD, CS modes over the entire drive route. The objective of the optimizer is to enable future Connected and Automated Vehicles (CAVs) to best utilize onboard energy for minimum overall energy consumption based on speed and elevation profile information from Intelligent Transportation Systems (ITS), Internet of Things (IoT), High-definition Mapping, and onboard sensing technologies. Emphasis is placed on runtime minimization to quickly react and plan an optimal mode scheme in highly dynamic road conditions with minimal computational resources. On-road performance of the…
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Control Strategy and Energy Recovery Potential for P2 Parallel Hybrid Step Gear Automatic Transmissions

Michigan Technological University-Darrell Robinette, Joshua Orlando
Published 2019-04-02 by SAE International in United States
The purpose of this investigation is to present a control strategy and energy recovery potential for P2 parallel hybrid step gear automatic transmissions. The automatic transmission types considered for the investigation are rear wheel drive 8 speed dual clutch transmission and 8 speed planetary automatic equipped each equipped with an electric motor between the engine and transmission. The governing equations of clutch-to-clutch upshift controls are presented and are identical for each transmission type. Various strategies are explored for executing the upshift under a range of input torques, shift times and engine torque management approaches. The differences in energy recovery potential based upon control strategy is explored piecewise as well as through a DFSS study. On a comprehensive drive cycle consisting of FTP 75, US06 and HWFET test cycles, it is shown that upshift regen torque management can be equivalent to approximately 0.8% of the total fuel energy used. Additionally, it is shown that the utilization of the P2 electric motor is a further enabler to reduced shift times and improved shift quality at part throttle…
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Computationally Efficient Reduced-Order Powertrain Model of a Multi-Mode Plug-In Hybrid Electric Vehicle for Connected and Automated Vehicles

Michigan Technological University-Neeraj Rama, Darrell Robinette
Published 2019-04-02 by SAE International in United States
This paper presents the development of a reduced-order powertrain model for energy and SOC estimation of a multi-mode plug-in hybrid electric vehicle using only vehicle speed profile and route elevation as inputs. Such a model is intended to overcome the computational inefficiencies of higher fidelity powertrain and vehicle models in short and long horizon energy optimization efforts such as Coordinated Adaptive Cruise Control (CACC), Eco Approach and Departure (EcoAND), Eco Routing, and PHEV mode blending. The reduced-order powertrain model enables Connected and Automated Vehicles (CAVs) to utilize the onboard sensor and connected data to quickly react and plan their maneuvers to highly dynamic road conditions with minimal computational resources. Although overall estimation accuracy is less than neural network and high-fidelity models, emphasis on runtime minimization with reasonable estimation accuracy enables energy optimization of CAVs without a need for computationally expensive server-based models. Performance of the model is evaluated on a fleet of second-generation Chevrolet Volts in a variety of driving scenarios and drive cycle durations. On-road testing indicates that the model can estimate actual vehicle…
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Torsional Vibration Analysis of Six Speed MT Transmission and Driveline from Road to Lab

Michigan Technological University-Jon Furlich, Jason Blough, Darrell Robinette
Published 2017-06-05 by SAE International in United States
When a manual transmission (MT) powertrain is subjected to high speeds and high torques, the vehicle driveshaft, and other components experience an increase in stored potential energy. When the engine and driveshaft are decoupled during an up or down shift, the potential energy is released causing clunk during the shift event. The customer desires a smooth shift thus reduction of clunk will improve experience and satisfaction. In this study, a six-speed MT, rear-wheel-drive (RWD) passenger vehicle was used to experimentally capture acoustic and vibration data during the clunk event. To replicate the in-situ results, additional data was collected and analyzed for powertrain component roll and pitch. A lumped parameter model of key powertrain components was created to replicate the clunk event and correlate with test data. The lumped parameter model was used to modify clutch tip-out parameters, which resulted in reduced prop shaft oscillations. By reducing the prop shaft oscillations the clunk phenomena can be reduced and customer satisfaction increased.
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