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The transport sector is one of the major contributors to greenhouse gas emissions. This study investigated three greenhouse gases emitted from road transport using a probe vehicle: CO₂, N₂O and CH₄ emissions as a function of cold start and ambient temperatures. A real-world driving cycle has been developed at Leeds and referred as LU-BS, which has an urban free flow driving pattern. The test vehicle was driven on the same route by the same driver on different days with different ambient temperatures. All the journeys were started from cold. An in-vehicle FTIR emission measurement system was installed on a EURO2 emission compliance SI car for emissions measurement at a rate of 0.5 Hz. This emission measurement system was calibrated on a standard CVS measurement system and showed an excellent agreement on the CO₂ measurement with the CVS results. The N₂O and CH₄ were calibrated by calibration gas bottles.

Understanding the creep and bolt load retention (BLR) behavior of promising Mg-Al alloys are crucial to developing elevated temperature resistance alloys. This is especially true for elevated temperature automotive applications with a prevalence of bolted joints. In this study, creep and fastener clamp load response of Mg-Al alloy AS41 was investigated and compared to that of Mg4Al and AS41 micro-alloyed with 0.15 % Ca. A compliance-creep approach was used to model the response of these Mg-Al alloys at bolted joints. The equation prediction of the BLR response and experimental results are in good agreement. AS41+0.15 Ca shows improved creep and BLR properties up to 175°C. A correlation between the microstructures, creep and BLR results reveal that the formation of a ternary CaMgSi phase is responsible for the improved elevated temperature behavior.

As one of the most important auto-body moving parts, door hinge is the key point of door design and its accessories arrangement, also the premise of the door kinematic analysis. We proposed an effective layout procedure for door hinge and developed an intelligent system on CATIA CAA platform to execute it. One toolbar and five function modules are constructed - Axis Arrangement, Section, Parting Line, Kinematic, Hinge Database. This system integrated geometrical algorithms, automatically calculate the minimum clearances between doors, fender and hinges on sections to judge if the layout is feasible. As the sizes of the clearances are set to 0s, the feasible layout regions and extreme start/end points are shown in parts window, which help the engineer to check the parting line and design a new one. Our system successfully implemented the functions of five modules for the layout of door hinge axis and parting line based on a door hinge database.

The European Commission (EC) as well as the United States Environmental Protection Agency (EPA) published legislations to regulate or encourage the use of low Global Warming Potential (GWP) refrigerants applied to Mobile Air Conditioning (MAC) systems. Europe mandates a GWP less than 150 of MAC refrigerants for new vehicle types. The thermodynamic refrigerant properties of R-1234yf are slightly different from the properties of R-134a, currently used in MAC systems. Although the basic material data show that R-1234yf is flammable, ignition tests performed for an automotive engine under-hood environment reveal design and packaging influences of its ignition behavior. After extensive collaborative research in 2009, the Society of Automotive Engineers Cooperative Research Team (SAE CRP1234) concluded that R-1234yf is suitable for use in automotive applications. Further ignition risk assessment regarding R-1234yf usage in MAC systems was done by SAE CRP1234-4 in 2013.

In this paper, a new computational method is provided to identify the uncertain parameters of Load Sensing Proportional Valve (LSPV) in a heavy truck brake system by using the polynomial chaos theory. The simulation model of LSPV is built in the software AMESim depending on structure of the valve, and the estimation process is implemented relying on the experimental measurements by pneumatic bench test. With the polynomial chaos expansion carried out by collocation method, the output observation function of the nonlinear pneumatic model can be transformed into a linear and time-invariant form, and the general recursive functions based on Newton method can therefore be reformulated to fit for the computer programming and calculation. To improve the estimation accuracy, the Newton method is modified with reference to Simulated Annealing algorithm by introducing the Metropolis Principle to control the fluctuation during the estimation process and escape from the local minima.

Developmental efforts are seeking to improve upon the efficiency and reliability of typical packed beds of sorbent pellets by using structured sorbents and alternative bed configurations. The benefits include increased structural stability gained by eliminating clay bound zeolite pellets that tend to fluidize and erode, and better thermal control during sorption leading to increased process efficiency. Test results that demonstrate such improvements are described and presented.

Human rated space vehicles must provide safe breathing air to the crew, in the event of fire or other upset that affects air quality. In very short missions, like those in Mercury, the crew could remain in their flight suit. As mission duration increased, some sort of emergency breathing apparatus was used to provide safe breathing air in emergency situations. The Orion vehicle has a unique set of emergency breathing apparatus design challenges: the vehicle is small compared to shuttle and station, the vehicle does not have a pressurized supply of breathing air, the vehicle has a 30% oxygen design limit, no airlocks or alternate habitable volumes, and during lunar missions the crew members need to remain in the vehicle for many hours after an emergency. A filtering respirator shows special promise to address the needs of Orion, but a filtering respirator for combustion products has never been built and qualified for space.

The underlying theories of both control engineering and real-time systems engineering assume idealized system abstractions that mutually neglect central aspects of the other discipline. Control engineering theory, on the one hand, usually assumes jitter free sampling and constant input-output latencies disregarding complex real-world timing effects. Real-time engineering theory, on the other hand, uses abstract performance models that neglect the functional behavior, and derives worst-case situations that have little expressiveness for control functionalities in physically dominated automotive systems. As a consequence, there is a lot of potential for a systematic co-engineering between both disciplines, increasing design efficiency and confidence. We have taken a standard control-engineering tool, Simulink, and combined it with state-of-the-art real-time system design and analysis tools, SymTA/S and TraceAnalyzer from Symtavision.

Power management of a hybrid energy storage system (HESS) with battery and supercapacitor(SC) is of critical importance for electric vehicles to achieve good driving performance, long traveling range and high energy efficiency. Due to the great differences in dynamic characteristics between battery and supercapacitor, and the complexity of a HESS, proper power management strategy between battery and supercapacitor remains to be challenging. The proposed research in this paper is to develop a power-balance and wavelet-transform based strategy for power distribution in a way such that each device can be utilized optimally. The transient dynamics is first decoupled via wavelet-transform algorithm while the power-balance algorithm is employed to improve system robustness based on the desired velocity-SOC relationship and a fuzzy logical controller. Finally some simulations have been conducted with results shown that the proposed strategy is valid and effective.

Electric vehicles are receiving considerable attention because they offer a more efficient and sustainable transportation alternative compared to conventional fossil-fuel powered vehicles. Since the battery pack represents the primary energy storage component in an electric vehicle powertrain, it requires accurate monitoring and control. In order to effectively estimate the battery pack critical parameters such as the battery state of charge (SOC), state of health (SOH), and remaining capacity, a high-fidelity battery model is needed as part of a robust SOC estimation strategy. As the battery degrades, model parameters significantly change, and this model needs to account for all operating conditions throughout the battery's lifespan. For effective battery management system design, it is critical that the physical model adapts to parameter changes due to aging.

Cooperative collision warning (CCW) systems use communication networks as a main component for creating situational awareness and eventually hazard detection. Simulation and analysis of such systems are generally more complicated due to the system being composed of components from very different domains of communication and vehicle safety. These components are inherently developed and modeled in different domains, as their basic operations are usually defined and engineered by researchers from different disciplines. Creating a simulation tool for CCW systems requires combining simulation models that are developed using different methodologies. As a result, a unified tool for study of such systems is not readily available. In this paper, we describe a co-simulation tool that models both components of communication and hazard prediction in one framework. The tool uses several different levels of abstraction for the communication model, while modeling the application in a precise manner.

A passive thermal management system (TMS) using composite phase change material (PCM) for large-capacity, rectangular lithium-ion batteries is designed. A battery module consisting of six Li-ion cells connected in series was investigated as a basic unit. The passive TMS for the module has three configurations according to the contact area between cells and the composite PCM, i.e., surrounding, front-contacted and side-contacted schemes. Firstly, heat generation rate of the battery cell was calculated using the Bernardi equation based on experimentally measured heat source terms (i.e. the internal resistance and the entropy coefficient). Physical and thermal properties such as density, phase change temperature, latent heat and thermal conductivity of the composite PCM were also obtained by experimental methods. Thereafter, thermal response of the battery modules with the three TMS configurations was simulated using 3D finite element analysis (FEA) modeling in ANSYS Fluent.

Dedicated Short Range Communications (DSRC) for vehicle-to-vehicle (V2V) cooperative applications for advanced safety is becoming a reality. Many automotive manufactures are entering advanced research phases or even planning deployments of such applications in the near future. However, the success of most V2V applications requires full or near-full deployment of the DSRC devices in new and existing vehicles, which will take many years to accomplish. In the meantime, use of autonomous sensors in combination with V2V can augment this deployment transitional period. In this paper we propose a hybrid approach that uses autonomous sensors to rebroadcast information about unequipped neighboring vehicles. In addition to messages that a host vehicle sends about its own state (such as position, speed, and direction), additional sensing capabilities also allow sending information about neighboring vehicles. This information can be obtained from radars, cameras and other autonomous sensors.

Modern cars feature a variety of different driving assistance systems, which aim to improve driving comfort and safety as well as fuel consumption. Due to the technical advances and the possibility to consider vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication, cooperative adaptive cruise control (CACC) strategies have received significant attention from both research and industrial communities. The performance of such systems can be enhanced if the future velocity of the surrounding traffic can be predicted. Generally, human driving behavior is a complex process and influenced by several environmental impacts. In this work a stochastic model of the velocity of a preceding vehicle based on the incorporation of available information sources such as V2I, V2V and radar information is presented. The main influences on the velocity prediction considered in this approach are current and previous velocity measurements and traffic light signals.

IEEE Standard 1609.2-2013, Security Services for Applications and Management Messages for Wireless Access in Vehicular Environments (WAVE), specifies its data structures and encoding using a proprietary language based on that used in the Internet Engineering Task Force (IETF)'s Transport Layer Security (TLS) specification. This approach is believed to allow fast encoding and decoding, but is non-standard, is not proved to be complete, lacks automatic tools for generation of codecs, and is difficult to extend. For these reasons, the 1609 Working Group approved the use of Abstract Syntax Notation 1 (ASN.1) for future versions of 1609.2, so long as ASN.1 did not significantly degrade performance. This paper is the first publication of the results of a performance analysis carried out to determine whether ASN.1-based encoding was in fact acceptable.

The idea of grid friendly charging is to use electricity from the grid to charge batteries when electricity is available in surplus and cheap. The goal is twofold: to avoid putting additional load on the electricity grid and to reduce the cost to the consumer. To achieve this, a smart meter and a tariff with variable electricity prices has to be in place. In Day Ahead tariff (DA), prices are announced in advance for the next day, and this information can be used to select the cheapest times to charge the battery by the required amount. The optimization method is very simple, and it only has to be run once per day. However, the balance of supply and demand is not fully known in advance. Therefore Real Time Pricing (RTP) tariff supplies electricity at spot market rate depending on the current balance.

This paper proposes an approach that characterizes a driver's driving behavior and style in real-time during car-following drives. It uses an online learning of the evolving Takagi-Sugeno fuzzy model combined with the Markov model. The inputs fed into the proposed algorithm are from the measured signals of on-board sensors equipped with current vehicles, including the relative distance sensors for Adaptive Cruise Control feature and the accelerometer for Electronic Stability Control feature. The approach is verified using data collected using a test vehicle from several car-following test trips. The effectiveness of the proposed approach has been shown in the paper.

This paper presents a nonlinear control approach to achieve good performances in vehicle path following and collision avoidance when the vehicle is driving under cruise highway conditions. Nonlinear model predictive control (NLMPC) is adopted to achieve online trajectory control based on a simplified vehicle model. GMRES/Continuation algorithm is used to solve the online optimization problem. Simulations show that the proposed controller is capable of tracking the desired path as well as avoiding the obstacles.

The increasing number of Plug-in Electric Vehicles (PEVs) impacts the power grid due to their high demand in power and energy, and uncertainties in the charging behavior. Typical PEVs are charged single-phase up to 32 A (7.2-kVA) or tri-phase up to 32 A (22.0- kVA). Both charging technologies have to be discussed in order to determine their impact on planning and operating of low-voltage distribution grids to assure a reliable and stable PEV charging. Traditional grid planning and analysis methods, which average and evenly distribute PEV loads on the distribution grid, fail in providing a realistic answer about the grid capacity to charge PEVs. The question; How many PEVs can be charged simultaneously on a distribution grid remains unanswered. Therefore, this paper describes a novel methodology to realistically evaluate the grid capacity for PEV charging on 3-phase 0.4-kV distribution grids.

This paper presents a vision based pedestrian detection system. The presented algorithm is a novel method that accurately segments the pedestrian regions in real time. The fact that the pedestrians are always vertically aligned is taken into consideration. As a result, the edge image is scanned from bottom to top and left to right. Both the color and edge data is combined in order to form the segments. The segmentation is highly dependent on the edge map. Even a single pixel dis-connectivity would lead to incorrect segments. To improve this, a novel edge linking method is performed prior to segmentation. The segmentation would consist of foreground and background segments as well. The background clutter is removed based on certain predefined conditions governed by the camera features. A novel edge based head detection method is proposed for increasing the probability of pedestrian detection. The combination of head and leg pattern will determine the presence of pedestrians.