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Improving vehicle response through advanced knowledge of traffic behavior can lead to large improvements in energy consumption for the single isolated vehicle. This energy savings across multiple vehicles can even be larger if they travel together as a cohort in harmonization. Additionally, if the vehicles have enough information about their immediate path of travel, and other vehicles’ in that path (and their respective critical forward-looking information), they can safely drive close enough to each other to share aerodynamic load. These energy savings can be upwards of multiple percentage points, and are dependent on several criteria. This analysis looks at criteria that contributes to energy savings for a cohort of vehicles in synchronous motion, as well as describes a study that allows for better understanding of the potential benefits of different types of cohorted vehicles in different platoon arrangements.

This paper presents an overview of the connected controls and optimization system for vehicle dynamics and powertrain operation on a light-duty plug-in multi-mode hybrid electric vehicle developed as part of the DOE ARPA-E NEXTCAR program by Michigan Technological University in partnership with General Motors Co. The objective is to enable a 20% reduction in overall energy consumption and a 6% increase in electric vehicle range of a plug-in hybrid electric vehicle through the utilization of connected and automated vehicle technologies. Technologies developed to achieve this goal were developed in two categories, the vehicle control level and the powertrain control level. Tools at the vehicle control level include Eco Routing, Speed Harmonization, Eco Approach and Departure and in-situ vehicle parameter characterization.

This paper details a study of the effects of multiple torque converter design and operating point parameters on the resistance of the converter to cavitation during vehicle launch. The onset of cavitation is determined by an identifiable change in the noise radiating from the converter during operation, when the collapse of cavitation bubbles becomes detectable by nearfield acoustical measurement instrumentation. An automated torque converter dynamometer test cell was developed to perform these studies, and special converter test fixturing is utilized to isolate the test unit from outside disturbances. A standard speed sweep test schedule is utilized, and an analytical technique for identifying the onset of cavitation from acoustical measurement is derived. Effects of torque converter diameter, torus dimensions, and pump and stator blade designs are determined.

Performing acoustic measurements on or near engines, transmissions, as well as in other circumstances where the environment is hazardous and harsh for microphones requires special precautions. Fluids inevitably leak, and the possibility of transducer damage can be very high without proper protection. Properly protecting microphones during testing allows for consistent data quality in these hazardous and difficult environments. While this paper will present the use of a 5 mil Nitrile cover which protects against many fluids within the scope of automotive testing, including water, hydrocarbons, and alcohols, as well as having good heat resistance and high strength, the concepts developed are applicable to other types of microphone protective mechanisms. Acoustic sensitivity was measured and used to calculate the change of the microphone's response after the treatment is applied, as well as after being exposed to various contaminants.

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.

This paper investigates the application of torque weighting to vibration dose value. This is done as a means to enhance correlation of perceived drive comfort directly to driver pedal commands while rejecting uncorrelated inputs. Current industry standards for vehicle comfort are formulated and described by ISO2631, which is a culmination of research with single or multi-axis vibration of narrow or broadband excitation. The standard is capable of estimating passenger comfort to vibrations, however, it only accounts for reaction vibrations to controlled inputs and not perceived vibration request vs. response vibration. Metrics that account for torque inputs and the vibration response create actionable estimates of dosage due to driver torque requests without uncorrelated inputs. This reduces the need for additional accelerometers and special compensating algorithms when road or track testing. The use case for the proposed modified metric is during the powertrain calibration process.

As automotive torque converters decrease in both diameter and axial length, the effects of cavitation in the torque converter becomes increasingly important on noise, efficiency, and performance goals. Cavitation is the formation and collapse of vapor bubbles in a working fluid when local static pressure falls below the vapor pressure of the working fluid. A technique to detect cavitation in automotive torque converters using nearfield acoustical measurements is presented. The technique concentrates on high frequency noise that is associated with the collapse of vapor bubbles. The nearfield acoustical technique is compared to two other techniques using static pressure measurements inside the torque converter; one on the torque converter stator blades and the other on the torque converter pump blades. A microwave telemetry transmitter was used to obtain data from inside the torque converter in both previous investigations.

As automotive torque converters decrease in both diameter and axial length, the effects of cavitation in the torque converter becomes increasingly important on noise, efficiency, and performance goals. Therefore, a cavitation prediction technique is developed in this investigation. In a previous investigation it was shown that cavitation is effected by inlet temperature, charge pressure, and K-factor. The prediction technique is devolved to encompass these variables. A dimensional analysis using the power product method is performed with all relevant variables. The nearfield acoustical cavitation detection technique, discussed in the previous investigation, is used to obtain experimental results from a torque converter test lab. The test matrix for the experimental results was constructed to include effects from inlet temperature, charge pressure, and K-factor. The data obtained experimentally is used to curve fit the results found through the power product method.

Predictive Signal Phase and Timing (SPAT) message set is one fundamental building block for vehicle-to-infrastructure (V2I) applications such as Eco-Approach and Departure (EAD) at traffic signal controlled urban intersections. Among the two complementary communication methods namely short-range sidelink (PC5) and long-range cellular radio link (Uu), this paper documents the work with long-range link: the complete data chain includes connecting to the traffic signals via existing backhaul communication network, collecting the raw signal phase state data, predicting the signal state changes and delivering the SPAT data via a geofenced service to requests over HTTP protocols. An Application Programming Interface (API) library is developed to support various cellular data transmission reduction and latency improvement techniques.

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.

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.

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.

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.

This paper presents a methodology that optimizes the periods of engine operation on a selected route for a Plug-in Hybrid Electric Vehicle (PHEV) or Hybrid Electric Vehicle (HEV) using Connected Vehicle data to minimize energy consumption. The study was conducted using a Reduced-Order Powertrain model of second-generation Chevrolet Volt. The method utilizes the Backward Induction Dynamic Programming algorithm to come up with an optimal control mode matrix of engine operation along the selected route for various battery states of charge. The objective of this method is to make use of Vehicle Connectivity to minimize the energy utilization of an HEV by using the speed and elevation profile of a selected route transmitted to the vehicle via V2X communication systems.

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.

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.

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.

Sound power can be determined using a variety of methods, but precision methods require the volume of the noise source to be less than 1% of the chamber volume leading to relatively large test chambers. Automotive torque converter performance and noise testing is completed in an enclosed metallic test fixture which inhibits the use of precision methods due to volume and space limitations. This paper describes a new method developed to accurately determine sound power of an automotive torque converter in a relatively small enclosure through characterization of the test environment. The test environment was characterized using two reference noise sources designed to represent torque converter noise output and physical geometry. Sound pressure levels of the sources were measured at multiple microphone locations and at three source amplitude levels to characterize the environment.

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.

This paper describes a methodology for investigating the controls coordination of clutch and propulsion torque sources relative to clutch energy, electrification energy consumption and output torque profile for offgoing controlled downshifts in P2 parallel xHEV powertrain configurations. The focus is on an 8 speed planetary automatic transmission, but the approach is equally applicable to any powerflow design with clutch-to-clutch shifting. The modeling technique is for an overall control strategy relative to achieving a targeted transmission input speed profile. A reduced order model of the transmission system is presented that accounts for input shaft acceleration and compensation of inertial contributions to offgoing clutch torque and transmission output torque.