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Direct injection offers a large number of degrees of freedom, as it strongly influences the mixture stratification process. Experiments on a single cylinder research engine fuelled by H2, carried out at Argonne National Laboratory, showed the influence of injection parameters (timing and geometry) on engine efficiency and combustion stability. At low load, when a late injection strategy was performed, an unstable engine behavior was detected varying the injection direction. In order to optimize the mixture stratification process in DI H2 engines, it is important to understand the physics underlying the experimental results. A spatially resolved representation of the in-cylinder processes is a useful tool to properly set the injection parameters. Also, the knowledge of the pre-injection flow field is of added value in optimizing the injection process.

Hydrogen is widely considered a promising fuel for future transportation applications for both, internal combustion engines and fuel cells. Due to their advanced stage of development and immediate availability hydrogen combustion engines could act as a bridging technology towards a wide-spread hydrogen infrastructure. Although fuel cell vehicles are expected to surpass hydrogen combustion engine vehicles in terms of efficiency, the difference in efficiency might not be as significant as widely anticipated [1]. Hydrogen combustion engines have been shown capable of achieving efficiencies of up to 45 % [2]. One of the remaining challenges is the reduction of nitric oxide emissions while achieving peak engine efficiencies. This paper summarizes research work performed on a single-cylinder hydrogen direct injection engine at Argonne National Laboratory.

For a series plug-in hybrid electric vehicle (PHEV), it is critical that batteries be sized to maximize vehicle performance variables, such as fuel efficiency, gasoline savings, and zero emission capability. The wide range of design choices and the cost of prototype vehicles calls for a development process to quickly and systematically determine the design characteristics of the battery pack, including its size, and vehicle-level control parameters that maximize the net present value (NPV) of a vehicle during the planning stage. Argonne National Laboratory has developed Autonomie, a modeling and simulation framework. With support from The MathWorks, Argonne has integrated an optimization algorithm and parallel computing tools to enable the aforementioned development process. This paper presents a study that utilized the development process, where the NPV is the present value of all the future expenses and savings associated with the vehicle.

This paper evaluates the impact of energy management strategy on the cost benefits of a plug-in hybrid electric vehicle (PHEV) by taking into account the impact of PHEV energy management on battery life and petroleum displacement over the life of the vehicle. Using Battery in the Loop (BIL), a real battery is subjected to transient power demands by a virtual vehicle. The vehicle energy management strategy is varied, resulting in different battery utilization scenarios. Battery life, which varies with battery utilization, is estimated for the different energy management scenarios. The same representative drive cycle is used over the different energy management strategies to isolate the impact of energy management on battery utilization. PHEV gasoline savings, in comparison to a charge sustaining hybrid, are calculated for each of the energy management strategies, for a fixed distance of 40 miles.

Plug-in hybrid electric vehicle (PHEV) technologies have the potential for considerable petroleum consumption reductions, possibly at the expense of increased tailpipe emissions due to multiple “cold” start events and improper use of the engine for PHEV specific operation. PHEVs operate predominantly as electric vehicles (EVs) with intermittent assist from the engine during high power demands. As a consequence, the engine can be subjected to multiple cold start events. These cold start events may have a significant impact on the tailpipe emissions due to degraded catalyst performance and starting the engine under less than ideal conditions. On current hybrid electric vehicles (HEVs), the first cold start of the engine dictates whether or not the vehicle will pass federal emissions tests. PHEV operation compounds this problem due to infrequent, multiple engine cold starts.

Lignin by-products from biorefineries has the potential to provide a low-cost alternative to petroleum-based precursors to manufacture carbon fiber, which can be combined with a binding matrix to produce a structural material with much greater specific strength and specific stiffness than conventional materials such as steel and aluminum. The market for carbon fiber is universally projected to grow exponentially to fill the needs of clean energy technologies such as wind turbines and to improve the fuel economies in vehicles through lightweighting. In addition to cellulosic biofuel production, lignin-based carbon fiber production coupled with biorefineries may provide $2,400 to $3,600 added value dry Mg−1 of biomass for vehicle applications. Compared to producing ethanol alone, the addition of lignin-derived carbon fiber could increase biorefinery gross revenue by 30% to 300%.

The paper presents a model-based approach to testing embedded automotive software systems in a real-time. Model-based testing approach relates to a process of creating test artifacts using various kinds of models. Real-time testing involves the use of a real-time environment to implement test application. Engineers shall use real-time testing techniques to achieve greater reliability and/or determinism in a test system. The paper contains an instruction how to achieve these objectives by proper definition, implementation, execution, and evaluation of test cases. The test cases are defined and implemented in a modeling environment. The execution and evaluation of test results is made in a real-time machine. The paper is concluded with results obtained from the initial deployment of the approach on a large scale in production stream projects.

In this paper, we present a real-time 360 degree surround system with parking aid feature, which is a very convenient parking and blind spot aid system. In the proposed system, there are four fisheye cameras mounted around a vehicle to cover the whole surrounding area. After correcting the distortion of four fisheye images and registering all images on a planar surface, a flexible stitching method was developed to smooth the seam of adjacent images away to generate a high-quality result. In the post-process step, a unique brightness balance algorithm was proposed to compensate the exposure difference as the images are not captured with the same exposure condition. In addition, a unique parking guidance feature is applied on the surround view scene by utilizing steering wheel angle information as well as vehicle speed information.

In the sensitive automotive applications like the safety restraint systems (SRS), twisted lines can be used to link the components of the system because of their property of reduction of the electromagnetic interference (EMI) coupling. Compared to the parallel lines, the twisted lines present the drawback to consume more copper in their manufacturing due to the greater length of their conductors. A parametric study based on the numerical modeling and the measurement of twisted lines is conducted in order to analyze the effect of the twisting pitch and of the untwisted part of these lines on the level of EMI coupling. This study will enable to optimize these two parameters in order to reduce the level of EMI coupling as well as the length of the conductors of the lines.

Shielding of the high voltage cabling is a cost effective method for reducing unwanted EMI in hybrid and electric vehicles. Ensuring the shielding effectiveness (SE) of the high voltage (HV) cabling and connectors is critical at the component and subsystem level. The effectiveness of the shielding must also be proven for the useful life of the vehicle. This paper will examine some of the critical aspects of ensuring good SE of HV cabling and connectors in hybrid and electric vehicles. This paper will also review some of the test methods utilized to make these measurements.

The presentation describes a technical solution for 100 Mbit/s Ethernet Data transmission cabling. This solution considers the specific requirements of automotive wiring harness and manufacturing. It bases on standard automotive connectors and headers. Currently the development of automotive electronic architecture considers central ECU or data backbone structure for the upcoming EE architecture (e. g. single ECU for network; SEN). For these structures solid and cost effective data backbone solutions are essential. Ethernet, a wide distributed and well-known bus system for office and industry data distribution provide a wide range of software tools and many physical layer solutions. Several cabling systems are available. Based on this we propose a solution for automotive application.

In hybrid and electric vehicles, the control of the electric motor is a critical component of vehicle functions such as motoring, generating, engine-starting and braking. The efficient and accurate control of motor torque is performed by the motor controller. It is a complex system incorporating sensor sampling, data processing, controls, diagnostics, and 3-phase Pulse Width Modulation (PWM) generation which are executed in sub-100 uSec periods. Due to the fast execution rates, care must be taken in the software coding phase to ensure the algorithms will not exceed the target processor's throughput capability. Production motor control development often still follows the path of customer requirements, component requirements, simulation, hand-code, and verification test due to the concern for processor throughput. In the case of vehicle system controls, typically executed no faster than 5-10 mSec periods, auto-coding tools are used for algorithm development as well as testing.

As fuel prices continue to rise automotive manufacturers continue to push their suppliers to provide technology that improves the potential fuel efficiency of their applications. In addition there is an increasing trend towards smaller, lighter and more compact vehicles to mitigate the automotive carbon footprint. These movements necessitated the development of a new compact, low mass, variable displacement compressor to match the requirements for these smaller and more efficient vehicles. The new Delphi MVC, or Miniature Variable Compressor, meets these requirements by integrating the high efficiency of our latest swashplate variable compressor design into a compact and lightweight package. This design can be offered in a range of displacements from 80 to 100cc and can be offered as either internally or externally controlled to support the customer's needs.

Similar to single-brick SCR architectures, the multi-brick SCR systems described in this paper require urea injection control software that meets the NOx conversion performance target while maintaining the tailpipe NH3 slip below a given threshold, under all driving conditions. The SCR architectures containing a close-coupled SCRoF and underfloor SCR are temperature-wise more favorable than the under-floor location and lead to significant improvement of the global NOx conversion, compared to a single-brick system. But in order to maximize the benefit of close-coupling, the urea injection control must maximize the NH3 stored in the SCRoF. The under-floor SCR catalyst can be used as an NH3 slip buffer, lowering the risk of NH3 slip at the tailpipe with some benefit on the global NOx conversion of the system. With this approach, the urea injection strategy has a limited control on the NH3 coverage of the under-floor SCR catalyst.

This paper includes analysis results for the control strategy of the Peugeot 3008 Hybrid4, a diesel-electric hybrid vehicle, under different thermal conditions. The analysis was based on testing results obtained under the different thermal conditions in the Advanced Powertrain Research Facility (APRF) at Argonne National Laboratory (ANL). The objectives were to determine the principal concepts of the control strategy for the vehicle at a supervisory level, and to understand the overall system behavior based on the concepts. Control principles for complex systems are generally designed to maximize the performance, and it is a serious challenge to determine these principles without detailed information about the systems. By analyzing the test results obtained in various driving conditions with the Peugeot 3008 Hybrid4, we tried to figure out the supervisory control strategy.

Production vehicles are commonly characterized and compared using fuel consumption (FC) and electric energy consumption (EC) metrics. Chassis dynamometer testing is a tool used to establish these metrics, and to benchmark the effectiveness of a vehicle's powertrain under numerous testing conditions and environments. Whether the vehicle is undergoing EPA Five-Cycle Fuel Economy (FE), component lifecycle, thermal, or benchmark testing, it is important to identify the vehicle and testing based variations of energy consumption results from these tests to establish the accuracy of the test's results. Traditionally, the uncertainty in vehicle test results is communicated using the variation. With the increasing complexity of vehicle powertrain technology and operation, a fixed energy consumption variation may no longer be a correct assumption.

Traditional vehicle air conditioning systems condition the entire cabin to a comfortable range of temperature and humidity regardless of the number of passengers in the vehicle. The A/C system is designed to have enough capacity to provide comfort for transient periods when cooling down a soaked car. Similarly for heating, the entire cabin is typically warmed up to achieve comfort. Localized heating and cooling, on the other hand, focuses on keeping the passenger comfortable by forming a micro climate around the passenger. This is more energy efficient since the system only needs to cool the person instead of the entire cabin space and cabin thermal mass. It also provides accelerated comfort for the passenger during the cooling down periods of soaked cars. Additionally, the system adapts to the number of passengers in the car, so as to not purposely condition areas that are not occupied.

This paper discusses the effect of the field stress variance on the value of demonstrated reliability in the automotive testing. In many cases the acceleration factor for a reliability demonstration test is calculated based on a high percentile automotive stress level, typically corresponding to severe user or environmental conditions. In those cases the actual field (‘true’) reliability for the population will be higher than that demonstrated by a validation test. This paper presents an analytical approach to estimating ‘true’ field reliability based on the acceleration model and stress variable distribution over the vehicle population. The method is illustrated by an example of automotive electronics reliability demonstration testing.

Power electronics products such as inverters and converters involve the use of Thermal Interface Materials (TIMs) between high power packages and a heat exchanger for thermal management. Conventional TIMs such as thermal greases, gels, solders and phase change materials (PCMs) face challenges to meet the need of these products to operate reliably at much higher temperatures. This has driven the development of new TIMs such as Transient Liquid Phase Sintering (TLPS) Conductive Adhesives. TLPS adhesives have been developed for many potential applications due to various advantages like lead free, flux-less and particularly their low temperature processability, which enables the use of heat sensitive components in the design. With all these motivations, a project was launched and completed to assess TLPS adhesives as a unique TIM for high temperature automotive applications due to its high bulk thermal conductivity and metallic joint formation at interfaces.

Response surface methodology (RSM) techniques were applied to develop a predictive model of electric vehicle (EV) energy consumption over the Environmental Protection Agency's (EPA) standardized drive cycles. The model is based on measurements from a synthetic composite drive cycle. The synthetic drive cycle is a minimized statistical composite of the standardized urban (UDDS), highway (HWFET), and US06 cycles. The composite synthetic drive cycle is 20 minutes in length thereby reducing testing time of the three standard EPA cycles by over 55%. Vehicle speed and acceleration were used as model inputs for a third order least squared regression model predicting vehicle battery power output as a function of the drive cycle. The approach reduced three cycles and 46 minutes of drive time to a single test of 20 minutes.