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In an effort to characterize the dynamics typical of school bus operation, National Renewable Energy Laboratory (NREL) researchers set out to gather in-use duty cycle data from school bus fleets operating across the country. Employing a combination of Isaac Instruments GPS/CAN data loggers in conjunction with existing onboard telemetric systems resulted in the capture of operating information for more than 200 individual vehicles in three geographically unique domestic locations. In total, over 1,500 individual operational route shifts from Washington, New York, and Colorado were collected. Upon completing the collection of in-use field data using either NREL-installed data acquisition devices or existing onboard telemetry systems, large-scale duty-cycle statistical analyses were performed to examine underlying vehicle dynamics trends within the data and to explore vehicle operation variations between fleet locations.

Smart technologies enabling connection among vehicles and between vehicles and infrastructure as well as vehicle automation to assist human operators are receiving significant attention as a means for improving road transportation systems by reducing fuel consumption – and related emissions – while also providing additional benefits through improving overall traffic safety and efficiency. For truck applications, which are currently responsible for nearly three-quarters of the total U.S. freight energy use and greenhouse gas (GHG) emissions, platooning has been identified as an early feature for connected and automated vehicles (CAVs) that could provide significant fuel savings and improved traffic safety and efficiency without radical design or technology changes compared to existing vehicles. A statistical analysis was performed based on a large collection of real-world U.S. truck usage data to estimate the fraction of total miles that are technically suitable for platooning.

This paper describes a front road wheel steer-by-wire system with two actuator motors on the rack and pinion assembly to move the road wheels. Dual actuators are used to provide actuator redundancy and to enhance the fault tolerance capability. When one actuator faults or fails, the other actuator is designed to work independently and maintain full system performance. The paper emphasizes control method to implement the motion control for the front road wheel steer-by-wire system with two actuators on the common load. The proposed dual servo synchronization motion control implements the angle tracking for the road wheel reference input by controlling two actuators synchronously and cooperatively. It includes two servo feedback control loops to track the common reference input. The angular position error between two feedback loops is compensated using a synchronized compensator.

The traditional method of engine knock detection is to compare the knock intensity with a predetermined threshold. The calibration of this threshold is complex and difficult. A statistical knock detection method is proposed in this paper to reduce the effort of calibration. This method dynamically calculates the knock threshold to determine the knock event. Theoretically, this method will not only adapt to different fuels but also cope with engine aging and engine-to-engine variation without re-calibration. This method is demonstrated by modeling and evaluation using real-time engine dynamometer test data.

Internal combustion engines are designed to maximize power subject to meeting exhaust emission requirements and minimizing fuel consumption. Maximizing engine power and fuel economy is limited by engine knock for a given air-to-fuel charge. Therefore, the ability to detect engine knock and run the engine at its knock limit is a key for the best power and fuel economy. This paper shows inaudible knock detection ability using in-cylinder ionization signals over the entire engine speed and load map. This is especially important at high engine speed and high EGR rates. The knock detection ability is compared between three sensors: production knock (accelerometer) sensor, in-cylinder pressure and ionization sensors. The test data shows that the ionization signals can be used to detect inaudible engine knock while the conventional knock sensor cannot under some engine operational conditions.

Low resolution fractional factorial experimental designs, used in screening, are more popular than ever due to the ever increasing costs of materials and machine time. Experimenters have to be more precise in their analysis, making every degree of freedom count. Resolution III designs are becoming more commonplace for use in screening designs. When running unsaturated resolution III designs there are extra degrees of freedom stemming from unassigned interactions. It is common practice to utilize these extra degrees of freedom to approximate error. In many cases, this common practice can over state the error and lead to erroneous results regarding factor statistical significance. Utilizing saturated resolution III designs and statistically analyzing unassigned interactions while estimating the error with replication is a method for strengthening the DOE strategy and improving the results from screening designs.

This paper introduces the Driver Stability System (DSS) at Visteon. DSS is a new active comfort / safety system for automobiles which controls the seat bolsters independently in real time to enhance the lateral support of the occupants. Under turning maneuvers, DSS reacts to the vehicle dynamics to provide an increased contact area between the occupants and their seats, allowing optimal occupant location with respect to such variables as steering wheel angle, lateral acceleration, yaw rate, and vehicle velocity. The lateral force compensation is directly coupled to the dynamic movement of vehicle chassis and the change of road profile. The system consists of the seat bolster assembly including DC motors, wheel speed sensors, steering wheel sensor, lateral accelerometer, yaw rate sensor, and electronic control unit (ECU). This paper also discusses the control concept of DSS and its realistic controller structure.

The present work demonstrates the application of Design of Experiments (DOE) statistical methods to the design and optimization of a hydraulic steering pump for NVH performance. DOE methods were applied to RPM-domain data to examine the effect of several different factors, as well as the interactions between these factors, on pump NVH. Whereas most DOE analyses typically consider only a single response variable, the present work considered multiple response variables. Specifically, pump NVH performance curves for several pump rotational orders over a range of shaft speeds were analyzed. Thus, it was possible to determine the effect of the factors in question over the entire speed range of pump operation, rather than a single speed or setting. Statistical methods were applied to determine which factors and interactions had a significant effect on pump NVH. These factors were used to construct an empirical mathematical prediction model for NVH performance.

Global Positioning System (GPS) data acquisition devices have proven useful tools for gathering real-world driving data and statistics. The data collected by these devices provide valuable information in studying driving habits and conditions. When used jointly with vehicle simulation software, the data are invaluable in analyzing vehicle fuel use and performance, aiding in the design of more advanced and efficient vehicle technologies. However, when employing GPS data acquisition systems to capture vehicle drive-cycle information, a number of errors often appear in the captured raw data samples. Common sources of error in GPS data include sudden signal loss, extraneous or outlying data points, speed drifting, and signal white noise, all of which combine to limit the quality of field data for use in downstream applications.

Estimation and prediction of residual life and reliability are serious concerns in life cycle management for aging structures. Laboratory testing replicating fatigue loading for a typical military aircraft wing skin was undertaken. Specimens were tested until their fatigue life expended reached 100% of the component fatigue life. Then, scanning electron microscopy was used to quantify the size and location of fatigue cracks within the high stress regions of simulated fastener holes. Distributions for crack size, nearest neighbor distances, and spatial location were characterized statistically in order to estimate residual life and to provide input for life cycle management. Insights into crack initiation and growth are also provided.

Steer-by-wire systems (SBW) offer the potential to enhance steering functionality by enabling features such as automatic lane keeping, park assist, variable steer ratio, and advanced vehicle dynamics control. The lack of a steering intermediate shaft significantly enhances vehicle architectural flexibility. These potential benefits led GM to include steer-by-wire technology in its next generation fuel cell demonstration vehicle, called “Sequel.” The Sequel's steer-by-wire system consists of front and rear electromechanical actuators, a torque feedback emulator for the steering wheel, and a distributed electronic control system. Redundancy of sensors, actuators, controllers, and power allows the system to be fault-tolerant. Control is provided by multiple ECU's that are linked by a fault-tolerant communication system called FlexRay. In this paper, we describe the objectives for fault tolerance and performance that were established for the Sequel.

The present work discusses the application of multivariate statistical methods for the analysis of NVH data. Unlike conventional statistical methods which generally consider single-value, or univariate data, multivariate methods enable the user to examine multiple response variables and their interactions simultaneously. This characteristic is particularly useful in the examination of NVH data, where multiple measurements are typically used to assess NVH performance. In this work, Principal Components Analysis (PCA) was used to examine the NVH data from a benchmarking study of hydraulic steering pumps. A total of twelve NVH measurements for each of 99 pump samples were taken. These measurements included steering pump orders and overall levels for vibration and sound pressure level at two microphone locations. Application of the PCA method made it possible to examine the entire set of data at once.

The present work demonstrates the application of Design of Experiments (DOE) statistical methods to the design and the improvement of a hydraulic steering pump noise, vibration, and harshness (NVH) performance in relief. DOE methods were applied to subjective ratings to examine the effect of several different factors, as well as the interactions between these factors on pump relief NVH. Specifically, the DOE was applied to the geometry of the cross ports on a hydraulic relief valve to improve “whistle” noise in the pump. Statistical methods were applied to determine which factors and interactions had a significant effect on pump whistle. These factors were used to produce a more robust cross port configuration reducing whistle noise. Lastly, the final configuration was experimentally verified on the test apparatus and subjectively confirmed in vehicle-level testing.

Commonly, a significant event is detected when a normally stable engine parameter (ex. sensor voltage, sensor current, air flow, pedal position, fuel level, tire pressure, engine acceleration, etc.) transiently exceeds a calibrated detection threshold. Many implementations of detection thresholds rely on multi-input lookup tables or functions and are complex and difficult to calibrate. An approach is presented to minimize threshold calibration effort and complexity, while improving detection performance, by dynamically computing thresholds on-line based on current real-time data. Determining engine synchronization without a camshaft position sensor is presented as an illustrative application.

Under a collaborative interagency agreement between the U.S. Environmental Protection Agency and the U.S. Department of Energy (DOE), the National Renewable Energy Laboratory (NREL) performed a series of in-depth analyses to characterize on-road driving behavior including distributions of vehicle speed, idle time, accelerations and decelerations, and other driving metrics of medium- and heavy-duty vocational vehicles operating within the United States. As part of this effort, NREL researchers segmented U.S. medium- and heavy-duty vocational vehicle driving characteristics into three distinct operating groups or clusters using real-world drive cycle data collected at 1 Hz and stored in NREL’s Fleet DNA database. The Fleet DNA database contains millions of miles of historical drive cycle data captured from medium- and heavy-duty vehicles operating across the United States. The data encompass existing DOE activities as well as contributions from valued industry stakeholder participants.

This work presents a methodology to determine the off-cycle fuel economy benefit of a 2-Layer HVAC system which reduces ventilation and heat rejection losses of the heater core versus a vehicle using a standard system. Experimental dynamometer tests using EPA drive cycles over a broad range of ambient temperatures were conducted on a highly instrumented 2016 Lexus RX350 (3.5L, 8 speed automatic). These tests were conducted to measure differences in engine efficiency caused by changes in engine warmup due to the 2-Layer HVAC technology in use versus the technology being disabled (disabled equals fresh air-considered as the standard technology baseline). These experimental datasets were used to develop simplified response surface and lumped capacitance vehicle thermal models predictive of vehicle efficiency as a function of thermal state.

Commercial vehicle fuel economy is known to vary significantly with both positive and negative road grade. Medium- and heavy-duty vehicles operating at highway speeds require incrementally larger amounts of energy to pull heavy payloads up inclines as road grade increases. Non-hybrid vehicles are unable to recapture energy on descent and lose energy through friction braking. While the on-road effects of road grade are well understood, the majority of standard commercial vehicle drive cycles feature no road grade requirements. Additionally, the existing literature offers a limited number of sources that attempt to estimate the on-road energy implications of road grade in the medium- and heavy-duty space. This study uses real-world commercial vehicle drive cycles from the National Renewable Energy Laboratory's Fleet DNA database to simulate the effects of road grade on fuel economy across a range of vocations, operating conditions, and locations.

To obtain the maximum output power and fuel economy from an internal combustion engine, it is often necessary to detect engine knock and operate the engine at its knock limit. This paper presents the ability to detect knock using in-cylinder ionization signals on a large displacement, air-cooled, “V” twin motorcycle engine over the engine operational map. The knock detection ability of three different sensors is compared: production knock (accelerometer) sensor, in-cylinder pressure sensor, and ionization sensor. The test data shows that the ionization sensor is able to detect knock better than the production knock sensor when there is high mechanical noise present in the engine.