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As the automotive industry prepares to roll out an unprecedented range of fully electric propulsion vehicle models over the next few years - it really brings to a head for folks responsible for brakes what used to be the subject of hypothetical musings and are now pivotal questions for system design. How do we really go about designing brakes for electric vehicles, in particular, for the well-known limit condition of descending a steep grade? What is really an “optimal’ design for brakes considering the imperatives for the entire vehicle? What are the real “limit conditions” for usage that drive the fundamental design? Are there really electric charging stations planned for or even already existing in high elevations that can affect regenerative brake capacity on the way down? What should be communicated to drivers (if anything) about driving habits for electric vehicles in routes with significant elevation change?

The Particulate Matter Index (PMI) is a tool that provides an indication of a fuel’s tendency to produce Particulate Matter (PM) emissions. Currently, the index is being used by various fuel laboratories and the Automotive OEMs as a tool to understand the gasoline fuel’s impact on both PM from engine hardware and vehicle-out emissions. In addition, a newer index that could be used to give an indication of the PM tendency of the gasoline range fuels, called the Particulate Evaluation Index (PEI), is shown to have a good correlation to PMI. The data used in those indices are collected from chemical analytical methods. This paper will compare gas chromatography (GC) methods used by three laboratories and discuss how the different techniques may affect the PMI and PEI calculation.

The purchase of a new automobile is unquestionably a significant investment for most customers, and with this recognition, comes a correspondingly significant expectation for quality and reliability. Amongst automotive systems -when it comes to considerations of reliability - the brakes (perhaps along with the tires) occupy a rarified position of being located in a harsh environment, subjected to continuous wear throughout their use, and are critical to the safe performance of the vehicle. Maintenance of the brake system is therefore a fact of life for most drivers - something that almost everyone must do, yet given the potentially considerable expense, it is something that of great benefit to minimize.

This study emphasizes the fact that there lies value and potential savings in harmonizing some of the inherent differences between the USA, EU, and China regulations with respect to the role of vehicle mass and lightweighting within Fuel Economy (FE) and Green House Gas (GHG) regulations. The definition and intricacies of FE and mass regulations for the three regions (USA, EU, and China) have been discussed and compared. In particular, the nuances of footprint-based, curb-mass-based, and stepped-mass-based regulations that lead to the differences have been discussed. Lightweighting is a customer benefit for fuel consumption, but in this work, we highlight cases where lightweighting, as a CO2 enabler, has incentives that do not align with rational customer values. A typical vehicle’s FE performance sensitivity to a change in mass on the standard regional certification drive cycles is simulated and compared across the three regions.

The diesel particulate filters (DPF) are considered the most robust technologies for particle emission reduction both in terms of mass and number. On the other hand, the increase of the backpressure in the exhaust system due to the accumulation of the particles in the filter walls leads to an increase of the engine fuel consumption and engine power reduction. To limit the filter loading, and the backpressure, a periodical regeneration is needed. Because of the growing interest about particle emission both in terms of mass, number and size, it appears important to monitor the evolution of the particle mass and number concentrations and size distribution during the regeneration of the DPFs. For this matter, in the presented work the regeneration of a catalyzed filter was fully analyzed. Particular attention was dedicated to the dynamic evolution both of the thermodynamic parameters and particle emissions.

More stringent emissions regulations are continually being proposed to mitigate adverse human health and environmental impacts of internal combustion engines. With that in mind, it has been proposed that vehicular particulate matter (PM) emissions should be regulated based on particle number in addition to particle mass. One aspect of this project is to study different sample handling methods for number-based aerosol measurements, specifically, two different methods for removing volatile organic compounds (VOCs). One method is a thermodenuder (TD) and the other is an evaporative chamber/diluter (EvCh). These sample-handling methods have been implemented in an engine test cell with a spark-ignited direct injection (SIDI) engine. The engine was designed for stoichiometric, homogeneous combustion.

There has been an increasing interest in exploring the potential to reduce energy consumption of future connected and automated vehicles. People have extensively studied various eco-driving implementations that leverage preview information provided by on-board sensors and connectivity, as well as the control authority enabled by automation. Quantitative real-world evaluation of eco-driving benefits is a challenging task. The standard regulatory driving cycles used for measuring exhaust emissions and fuel economy are not truly representative of real-world driving, nor for capturing how connectivity and automation might influence driving trajectories. To adequately consider real-world driving behavior and potential “off-cycle” impacts, this paper presents four collaborative evaluation methods: large-scale simulation, in-depth simulation, vehicle-in-the-loop testing, and vehicle road testing.

This report describes a new driving simulator capability at General Motors (GM) Research and Development's (R&D) Vehicle Development Research (VDR) Laboratory and its application in an iterative HMI development process. The paper also provides an overview of three recent simulator usability tests supporting HMI development.

In the previous research1), the authors discovered that the sudden pressure increase phenomenon in diesel particulate filter (DPF) was a result of soot collapse inside DPF channels. The proposed hypothesis for soot collapse was a combination of factors such as passive regeneration, high humidity, extended soak period, high soot loading and high exhaust flow rate. The passive regeneration due to in-situ NO2 and high humidity caused the straw like soot deposited inside DPF channels to take a concave shape making the collapse easier during high vehicle acceleration. It was shown that even if one of these factor was missing, the undesirable soot collapse and subsequent back pressure increase did not occur. Currently, one of the very popular NOx reduction technologies is the Selective Catalytic Reduction (SCR) on Filter which does not have any platinum group metal (PGM) in the washcoat.

The impact of gasoline composition on vehicle particulate emissions response has been widely investigated and documented. Correlation equations between fuel composition and particulate emissions have also been documented, e.g. Particulate Matter Index (PMI) and Particulate Evaluation Index (PEI). Vehicle PM/PN emissions correlate very well with these indices. In a previous paper, global assessment with PEI on fuel sooting tendency was presented [1]. This paper will continue the previous theme by the authors, and cover China gasoline in more detail. With air pollution an increasing concern, along with more stringent emission requirements in China, both OEMs and oil industries are facing new challenges. Emissions controls require a systematic approach on both fuels and vehicles. Chinese production vehicle particulate emissions for a range of PEI fuels are also presented.

The implementation of electronic shifters (e-shifter) for automatic transmissions in vehicles has created many new opportunities for the customer facing transmission interface and in-vehicle packaging. E-shifters have become popular in recent years as their smaller physical size leads to packaging advantages, they reduce the mass of the automatic transmission shift system, they are easier to install during vehicle assembly, and act as an enabler for autonomous driving. A button-style e-shifter has the ability to create a unique customer interface to the automatic transmission, as it is very different from the conventional column lever or linear console shifter. In addition to this, a button-style e-shifter can free the center console of valuable package space for other customer-facing functions, such as storage bins and Human-Machine Interface controllers.

Automotive technology is rapidly changing with electrification of vehicles, driver assistance systems, advanced safety systems etc. This advancement in technology is making the task of validation and verification of embedded software complex and challenging. In addition to the component testing, integration testing imposes even tougher requirements for software testing. To meet these challenges dSPACE is continuously evolving the Hardware-In-the-Loop (HIL) technology to provide a systematic way to manage this task. The paper presents developments in the HIL hardware technology with latest quad-core processors, FPGA based I/O technology and communication bus systems such as Flexray. Also presented are developments of the software components such as advanced user interfaces, GPS information integration, real-time testing and simulation models. This paper provides a real-world example of implication of integration testing on HIL environment for Chassis Controls.

There is higher and higher demand by customers for vehicles with the maximum level of comfort, this aspect being a target to be achieved together with the general trend to increase performance and also with the necessity to reduce engine out emissions to satisfy the new environmental regulations. GMDAT has recently developed new EU5 2.0 and 2.2 liter L4-cylinder turbocharged Diesel engines that, to address customer demands, have improved power, lower exhaust gas emissions and NVH performance aligned to best in class in its segment. With the final aim of making this engine best in class from an NVH perspective, the NVH development has been executed in a very structured way, going through target setting and deployment, concept and design, combustion and mechanical development through computational analysis first and subsequently experimental tests.

The objective of this research is a detailed investigation of particulate sizing and number count from a spark-ignited, direct-injection (SIDI) engine at different operating conditions. The engine is a 549 [cc] single-cylinder, four-valve engine with a flat-top piston, fueled by Tier II EEE. A baseline engine operating condition, with a low number of particulates, was established and repeatability at this condition was ascertained. This baseline condition is specified as 2000 rpm, 320 kPa IMEP, 280 [°bTDC] end of injection (EOI), and 25 [°bTDC] ignition timing. The particle size distributions were recorded for particle sizes between 7 and 289 [nm]. The baseline particle size distribution was relatively flat, around 1E6 [dN/dlogDp], for particle diameters between 7 and 100 [nm], before dropping off to decreasing numbers at larger diameters. Distributions resulting from a matrix of different engine conditions were recorded.

Variable valve actuation is a focus to improve fuel efficiency for passenger car engines. Various means to implement early and late intake valve closing (E/LIVC) at lower load operating conditions is investigated. The study uses GT Power to simulate on E/LIVC on a 2.5 L gasoline engine, in-line four cylinder, four valve per cylinder engine to evaluate different ways to achieve Atkinson cycle performance. EIVC and LIVC are proven methods to reduce the compression-to-expansion ratio of the engine at part load and medium load operation. Among the LIVC strategies, two non-traditional intake valve lift profiles are investigated to understand their impact on reduction of fuel consumption at low engine loads. Both the non-traditional lift profiles retain the same maximum lift as a normal intake valve profile (Otto-cycle) unlike a traditional LIVC profile (Atkinson cycle) which needs higher maximum lift.

Understanding customer expectations is critical to satisfying customers. Holding customer clinics is one approach to set winning targets for the engineering functional measures to drive customer satisfaction. In these clinics, customers are asked to operate and interact with vehicle systems or subsystems such as doors, lift gates, shifters, and seat adjusters, and then rate their experience. From this customer evaluation data, engineers can create customer loss or preference functions. These functions let engineers set appropriate targets by balancing risks and benefits. Statistical methods such as cumulative customer loss function are regularly applied for such analyses. In this paper, a new approach based on the Taguchi method is proposed and developed. It is referred to as Taguchi Customer Loss Function (TCLF).

The comfort assessment of seats in the automotive industry has historically been accomplished by subjective ratings. This approach is expensive and time consuming since it involves multiple prototype seats and numerous people in supporting processes. In order to create a more efficient and robust method, objective metrics must be developed and utilized to establish measurable boundaries for seat performance. Objective measurements already widely accepted, such as IFD (Indentation Force Deflection) or CFD (Compression Force Deflection) [1], have significant shortcomings in defining seat comfort. The most obvious deficiency of these component level tests is that they only deal with a seats' foam rather than the system response. Consequently, these tests fail to take into account significant factors that affect seat comfort such as trim, suspension, attachments and other components.

This paper describes the design of a multivariable, constrained Model Predictive Control (MPC) system for torque tracking in turbocharged gasoline engines scheduled for production by General Motors starting in calendar year 2018. The control system has been conceived and co-developed by General Motors and ODYS. The control approach consists of a set of linear MPC controllers scheduled in real time based on engine operating conditions. For each MPC controller, a linear model is obtained by system identification with data collected from engines. The control system coordinates throttle, wastegate, intake and exhaust cams in real time to track a desired engine torque profile, based on measurements and estimates of engine torque and intake manifold pressure.

Although advanced driver assistance systems (ADAS) have been widely introduced in automotive industry to enhance driving safety and comfort, and to reduce drivers’ driving burden, they do not in general reflect different drivers’ driving styles or customized with individual personalities. This can be important to comfort and enjoyable driving experience, and to improved market acceptance. However, it is challenging to understand and further identify drivers’ driving styles due to large number and great variations of driving population. Previous research has mainly adopted physical approaches in modeling drivers’ driving behavior, which however are often very much limited, if not impossible, in capturing human drivers’ driving characteristics. This paper proposes a reinforcement learning based approach, in which the driving styles are formulated through drivers’ learning processes from interaction with surrounding environment.

This paper studies the use of active rear steering (4-wheel steering) to change the transient lateral dynamics and body motion of passenger cars in the stable or linear region of the tires. Rear steering systems have been used for several decades to improve low speed turning maneuverability and high speed stability, and various control strategies have been previously published. With a model-based, feed-forward rear steer control strategy, the lateral transient can be influenced separately from the steady-state steering gain. This lateral transient is influenced by many vehicle parameters, but we will look at the influence of active rear steer and various tire types such as all-season, snow, and summer. This study will explore the ability for a rear steering system to change the lateral transient to a step steer input, compared to the effect of changing tire types.