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Electrification is the well-accepted solution to address carbon emissions and modernize vehicle controls. Batteries play a critical in the journey of electrification and modernization with battery voltage prediction as the foundation for safe and efficient operation. Due to its strong dependency on prior information, battery voltage was estimated with recurrent neural network methods in the recent literatures exploring a variety of deep learning techniques to estimate battery behaviors. In these studies, standard recurrent neural networks, gated recurrent units, and long-short term memory are popular neural network architectures under review. However, in most cases, each neural network architecture is individually assessed and therefore the knowledge about comparative study among three neural network architecture is limited. In addition, many literatures only studied either the dynamic voltage response or the voltage relaxation.

Computer programs and models are playing an increasing role in simulating vehicle crashworthiness, dynamic, and fuel efficiency. To maximize the effectiveness of these models, the validity and predictive capabilities of these models need to be assessed quantitatively. For a successful implementation of Computer Aided Engineering (CAE) models as an integrated part of the current vehicle development process, it is necessary to develop objective validation metric that has the desirable metric properties to quantify the discrepancy between multiple tests and simulation results. However, most of the outputs of dynamic systems are multiple functional responses, such as time history series. This calls for the development of an objective metric that can evaluate the differences of the multiple time histories as well as the key features under uncertainty.

As the world's largest auto producer and consumer, China is both the most promising and complex market given the country's rapid economic growth, huge population, and many regional and segment preference differences. This research is aimed at developing data-driven demand models for customer preference analysis and prediction under a competitive market environment. Regional analysis is first used to understand the impact of geographical factors on customer preference. After a comprehensive data exploration, a customer-level mixed logit model is built to shed light on fast-growing vehicle segments in the Chinese auto market. By combining the data of vehicle purchase, consideration, and past choice, cross-shopping behaviors and brand influence are explicitly modeled in addition to the impact of customer demographics, usage behaviors, and attributes of vehicles.

Exhaust pressures (P3) are hard parameters to measure and can be readily estimated, the cost of the sensors and the temperature in the exhaust system makes the implementation of an exhaust pressure sensor in a vehicle control system a costly endeavor. The contention with measured P3 is the accuracy required for proper engine and vehicle control can sometimes exceed the accuracy specification of market available sensors and existing models. A turbine inlet exhaust pressure observer model based on isentropic expansion and heat transfer across a turbocharger turbine was developed and investigated in this paper. The model uses 4 main components; an open loop P3 orifice flow model, a model of isentropic expansion across the turbine, a turbine and pipe heat transfer models and an integrator with the deviation in the downstream turbine outlet parameter.

Dynamic vehicle loads play critical roles for automotive controls including battery management, transmission shift scheduling, distance-to-empty predictions, and various active safety systems. Accurate real-time estimation of vehicle loads such as those due to vehicle mass and road grade can thus improve safety, efficiency, and performance. While several estimation methods have been proposed in literature, none have seen widespread adoption in current vehicle technologies despite their potential to significantly improve automotive controls. To understand and bridge the gap between research development and wider adoption of real-time load estimation, this paper assesses the accuracy and performance of four estimation methods that predict vehicle mass and/or road grade.

The ability to operate a spark-ignition (SI) engine near the knock limit provides a net reduction of engine fuel consumption. This work presents a real-time knock control system based on stochastic knock detection (SKD) algorithm. The real-time stochastic knock control (SKC) system is developed in MATLAB Simulink, and the SKC software is integrated with the production engine control strategy through ATI's No-Hooks. The SKC system collects the stochastic knock information and estimates the knock level based on the distribution of knock intensities fitting to a log-normal (LN) distribution. A desired knock level reference table is created under various engine speeds and loads, which allows the SKC to adapt to changing engine operating conditions. In SKC system, knock factor (KF) is an indicator of the knock intensity level. The KF is estimated by a weighted discrete FIR filter in real-time.

There have been many articles published in the last decade or so concerning the components of an electronic stability control (ESC) system, as well as numerous statistical studies that attempt to predict the effectiveness of such systems relative to crash involvement. The literature however is free from papers that discuss how engineers might develop such systems in order to achieve desired steering, handling, and stability performance. This task is complicated by the fact that stability control systems are very complex and their designs and what they can do have changed considerably over the years. These systems also differ from manufacturer to manufacturer and from vehicle to vehicle in a given maker of automobiles. In terms of ESC hardware, differences can include all the components as well as the addition or absence of roll rate sensors or active steering gears to name a few.

As vehicle fuel economy continues to grow in importance, the ability to accurately measure the level of efficiency on all driveline components is required. A standardized test procedure enables manufacturers and suppliers to measure component losses consistently and provides data to make comparisons. In addition, the procedure offers a reliable process to assess enablers for efficiency improvements. Previous published studies have outlined the development of a comprehensive test procedure to measure transfer case speed-dependent parasitic losses at key speed, load, and environmental conditions. This paper will take the same basic approach for the Power Transfer Units (PTUs) used on Front Wheel Drive (FWD) based All Wheel Drive (AWD) vehicles. Factors included in the assessment include single and multi-stage PTUs, fluid levels, break-in process, and temperature effects.

Emissions sample probes are widely used in engine and vehicle emissions development testing. Tailpipe bag summary data is used for certification, but the time-resolved (or modal) emissions data at various points along the exhaust system is extremely important in the emission control technology development process. Exhaust gas samples need to be collected at various locations along the exhaust aftertreatment system. Typically, a tube with a small diameter is inserted inside the exhaust pipe to avoid any significant effect on flow distribution. The emissions test equipment draws a gas sample from the exhaust stream at a constant volumetric flow rate (typically around 10 SLPM). The sample probe tube delivers exhaust gas from the exhaust pipe to emissions test equipment through multiple holes on the surface of tube. There can be multiple rows of holes at different axial planes along the length of the sample probe as well as multiple holes on a given axial plane of the sample probe.

We present research in progress to develop and implement a transportable instrumentation package (TIP) to collect driver data in a vehicle. The overall objective of the project is to investigate the symbiotic relationship between humans and their vehicles. We first describe the state-of-art technologies to build the components of TIP that meet the criteria of ease of installation, minimal interference with driving, and sufficient signals to monitor driver state and condition. This method is a viable alternative to current practice which is to first develop a fully instrumented test vehicle, often at great expense, and use it to collect data from each participant as he/she drives a prescribed route. Another practice, as for example currently being used in the SHRP-2 naturalistic driving study, is to install the appropriate instrumentation for data collection in each individual's vehicle, often requiring several hours.

This paper reports a study undertaken by the Crash Safety Working Group (CSWG) of the United States Council for Automotive Research (USCAR) to determine generic acceleration pulses for testing and evaluating advanced batteries subjected to inertial loading for application in electric passenger vehicles. These pulses were based on characterizing vehicle acceleration time histories from standard laboratory vehicle crash tests. Crash tested passenger vehicles in the United States vehicle fleet of the model years 2005-2009 were used in this study. Crash test data, in terms of acceleration time histories, were collected from various crash modes conducted by the National Highway Traffic Safety Administration (NHTSA) during their New Car Assessment Program (NCAP) and Federal Motor Vehicle Safety Standards (FMVSS) evaluations, and the Insurance Institute for Highway Safety (IIHS).

The tremendous growth of complexity in automotive control system electronics in the past 30 years has driven the industry to employ ever more advanced development techniques, ranging from formally managing functional architecture to employing more sophisticated functional safety development processes. The industry now finds itself facing emerging trends that will include more vehicle electrification, connectivity, personalization, and automation. Contextual and location awareness will also play larger roles. In light of these trends, vehicle control development processes will need to continue to evolve. This paper will explore some of the challenges that automakers will face as they move to incorporate these new technologies.

As vehicle fuel economy continues to grow in importance, the ability to accurately measure the level of parasitic losses on all driveline components is required. A standardized comparison procedure enables manufacturers and suppliers to measure component losses consistently, in addition to offering a reliable process to assess enablers for efficiency improvements. This paper reviews the development of a comprehensive test procedure to measure transfer case speed-dependent parasitic losses at key speed, load, and environmental conditions. This procedure was validated for repeatability considering variations in soak time, temperature measurement positions on the transfer case, and test operating conditions. Additional assessments of spin loss at low ambient temperatures, and the effect of component break-in on spin loss were also conducted.

Several emission performance tests like Butane Working Capacity (BWC), Cycle Life, and ORVR load tests are required for the certification of a vehicle; these tests are both expensive and time consuming. This paper presents a test process based upon analytical simulation of BWC of an automotive carbon canister in order to greatly reduce the cost incurred in physical tests. The computational model for the fixed-bed system of a carbon canister is based upon non-equilibrium, non-Isothermal, and non-adiabatic algorithm to simulate the real life loading/purging of hydrocarbon vapors from this device.

The automotive industry continues to develop new powertrain technologies aimed at reducing overall vehicle level fuel consumption. This paper discusses the development of a new highly efficient parallel hybrid transmission for use in transversely installed powertrains for FWD applications. FEV is developing a new 7-speed hybrid transmission for transverse installation. The transmission with a design torque of 320 Nm is based on AMT (automated manual transmission) technology and uses a single electric motor. The innovative gearset layout combines the advantages of modern AMTs such as best efficiency, low costs and few components (reduced part count) with full hybrid capabilities and electric torque support during all gear shifts. Furthermore, the gear set layout allows for very short shift-times due to the favorable distribution of inertias. Other features include an A/C compressor being electrically driven by the electric motor of the transmission during engine start/stop phases.

The presentation offers a brief history of the electric vehicle and parallels the realities of those early vehicles with the challenges and solutions of the electrified vehicles coming to market today. A technology evolution for every major component of these vehicles has now made this mode of transportation viable. The Focus Electric is Ford's first electric passenger car utilizing the advanced technology developments to meet the needs of electric car buyers in this emerging market. Presenter Charles Gray, Ford Motor Co.

Most people still remember the introduction of the IBM PC in 1981 and the first Microsoft Windows operating system in 1985. These were the pioneering technologies that started a revolution in automotive test equipment in the service bay. What was once a purely mechanical garage environment where information was published annually in large paper manuals has evolved into a highly technical computing environment. Today vehicle networks link onboard vehicle control systems with diagnostic systems and updated service information is published daily over the Internet. A lot has changed over the last twenty years, and manufacturers of diagnostic test equipment are learning to deal with the constantly evolving computing platforms and host operating systems. This paper traces the history of automotive diagnostic equipment at Ford Motor Company and shares some of the hard lessons learned from the early systems.

The Auto Industry is responding to the environment and energy conservation concerns by ramping up production of hybrid electric vehicles (HEV). As the initial hurdles of making the powertrain operate are overcome, challenges such as making the powertrain feel more refined and intuitive remain. This paper investigates one of the key parameters for delivering that refinement: engine RPM behavior. Ideal RPM behavior is explored and included in the design of a control system. System implications are examined with regard to the effect of engine RPM scheduling on Battery usage and vehicle responsiveness.

Hybrid electric vehicle (HEV) powertrains have become key to developing environmentally friendly and fuel efficient vehicles. As such, companies are continually investing in developing new hybrid powertrain architectures. Ford Motor Company has developed a new “Dual-Drive” full hybrid electric vehicle that overcomes some attribute deficiencies of existing hybrid powertrain architectures due to the kinematic arrangement of the engine, motors and driveline components. This hybrid powertrain is comprised of conventional powertrain components as its base with an electric motor on the rear axle, and a crank integrated starter generator, engine and transmission on the front axle. It forms a complex configuration which provides fuel economy improvement over a conventional powertrain.

Magnesium alloy extrusions offer potentially more mass saving compared to magnesium castings. One of the tasks in the United States Automotive Materials Partnership (USAMP) ?Magnesium Front End Research and Development? (MFERD) project is to evaluate magnesium extrusion alloys AM30, AZ31 and AZ61 for automotive body applications. Solid and hollow sections were made by lowcost direct extrusion process. Mechanical properties in tension and compression were tested in extrusion, transverse and 45 degree directions. The tensile properties of the extrusion alloys in the extrusion direction are generally higher than those of conventional die cast alloys. However, significant tension-compression asymmetry and plastic anisotropy need to be understood and captured in the component design.