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This paper proposes an automatic corrective safety controller design and evaluation based on braking/traction actuation to enhance the stability of a ground vehicle subjected to a tire blowout. Along with the nonlinear Dugoff’s tire model, a nonlinear planar seven degrees of freedom control-oriented vehicle model is developed and validated using MSC Adams/car package. The proposed novel control-oriented model accounts for the longitudinal dynamics, large steering and slip angles, and the nonlinearities associated with the vehicle/tire coupled system. In consequence, a distributive torque control technique in the framework of the integral terminal sliding mode controller is established. The integral action is employed in the sliding surfaces to enhance the steady-state tracking performance of the closed-loop system. The controller distributes the control torque demand among the three inflated tires excluding the blown tire to counteract the blowout-induced yawing disturbance. Two control strategies are introduced to facilitate controller practical implementation in both electric and conventional vehicles. The results indicate that the proposed controller is perfectly competent to stabilize the vehicle and robustly track the desired trajectory in a straight line and curvilinear motions as well as under nonlinear operating conditions.

Lightwiegh materials and vehicles' electrification are among the most viable and economic solutions to improve fuel ecocnmoy of vehicles and reduce environmental impacts in the operational phase of typical vehicle's life cycle span. This study aims to shed more light on the combined effect of lightweighing and electrification by assessing different lightweight designs and electric powetrians from the environmental perspective using a life cycle analysis coupled with an emphasis on energy expenditures and carbon dioxide emissions. This paper discusses the life cycle assessment for several advanced powertrains namely; plug-in hybrid electric vehicles (PHEV), battery electric vehicles (BEV) and hybrid electric vehicles (HEV) relative to the conventional gasoline operated internal combustion engine based power train vehicles. The main focus will be on the energy greenhouse gas emissions (GHG) in the material extraction and resources phase, manufacturing phase and use phase (operation and maintenance). While most of the current studies focus on the use phase that does not reflect the correct environmental impacts associated with advanced powertrains, thus the presented text applies a holistic LCA approach that covers pre-manufacturing, manufacturing, operational and end-of-life phases, plus another indirect phase to account for fuel extraction, refining and transportation to the end-users or customers. Based on the LCA emissions results, one may infer that environmental policies that reduce emissions rates from the electricity sector can mitigate this effect without completely eliminating it. Interestingly, the analysis show that lightweight vehicles with internal combustion engines have less impacts on the environment as a direct result of upstream emissions associated with electricity generation in United States. This scenario can differ in other countries with higher renewable and sustainable energy generated electric powers.

Hybridization of automotive powertrains by using more than one type of energy converter is considered as an important step towards reducing fuel consumption and air pollutants. Specifically, the development of energy efficient, highly complex, alternative drive-train systems, in which the interactions of different energy converters play an important role, requires new design methods and processes. This paper discusses the inclusion of an alternative hybrid power train into an existing vehicle platform for maximum energy efficiency. The new proposed integrated Vehicle Hardware In-the-loop (VHiL) and Model Based Design (MBD) approach is utilized to evaluate the energy efficiency of electrified powertrain. In VHiL, a complete chassis system becomes an integrated part of the vehicle test bed. A complete conventional Internal Combustion Engine (ICE) powered vehicle is tested in roller bench test for the integration of energy efficient hybrid electric power train modules in closed-loop, real-time, feedback configuration. A model that is a replica of the test vehicle is executed – in real-time- where all hybrid power train modules are included. While the VHiL platform is controlling the signal exchange between the test bed automation software and the vehicle on-board controller, the road load exerted on the driving wheels is manipulated in closed –loop real-time manner in order to reflect all hybrid driving modes including: All Electric Range (AER), Electric Power Assist (EPA) and blended Modes (BM). Upon successful implementation of VHiL, a comparative study between Rule Based (RB) energy management strategy (EMS) and Equivalent Consumption Minimization Strategy (ECMS) to Control Parallel Through-The-Road Hybrid Electric Vehicle (PTTR-HEV) is performed. The study shows that the actual fuel efficiency of the tested vehicle under both control strategies can be used in order to evaluate the effectiveness of energy conversion efficiency of the powertrain system. The fuel consumption of hybridized powertrain is compared with the conventional powertrain equipped in an actual vehicle to help comprehend the degree of efficiency attained by the hybridization. This process is developed in order to enable effective tuning/validation of advanced energy management strategies utilized in hybrid electric powertrain through an evaluation of a complete real chassis system subject to electric hybridization. The VHiL is considered as new evolution for the utilization of vehicle test bed as a predictive mechatronic platform for the development of energy efficient electrified propulsion systems and thus reduce cost and time.

Cylindrical (type: 26650) Li-ion cells (LiFePO 4 cathodes) currently used in the electric vehicles (EVs), plug-in hybrid electric vehicles etc. were subjected to simulated federal urban driving schedule at 25 and 50 °C for performance evaluation. Drive profiles (current versus time) for charge sustaining and charge depleting modes were derived from the federal urban driving schedule velocity profiles considering acceleration, regenerative braking, rolling resistance, drag force etc. for typical plug-in hybrid electric vehicles. In particular, the batteries were cycled extensively at 50 °C under charge sustaining as well as charge depleting modes to monitor capacity values, followed by analyzing the LiFePO 4 cathode material by X-ray diffraction analysis. The capacity degradation was found to be very significant in both the modes with 13 and 19% under charge sustaining and charge depleting modes after 337 and 1007 cycles, respectively at elevated temperature. High frequency resistance values measured by electrochemical impedance spectroscopy were found to increase significantly under high temperature cycling, leading to power fading. As evident from Rietveld analysis, phase change in LiFePO 4 is observed beyond 1000 cycles at elevated temperature under charge depleting mode, with the observation of FePO 4 from the powder diffraction data of the cathodes from the cycled cells. In addition, there was also significant change in crystallite size of the cathode active materials after charge/discharge cycling under charge depleting mode.

The Arizona State University EcoCAR-3 team is a new team in Advanced Vehicle Technology Competitions (AVTCs), competing among 16 North American Universities under a 4 year competition aimed at redesigning a high performance conventional vehicle into a hybrid electric vehicle, reducing the environmental impacts while maintaining the performance of the vehicle. The team imitates General Motors (GM) Vehicle Development Process (VDP) in designing, building and refining the vehicle. The first step in design process is Powertrain Architecture selection, and the team is designing a parallel pre-transmission plug-in hybrid vehicle to meet the competition targets. The proposed powertrain consists of a 2.4L gasoline (E85) engine, a 140 kW electric motor, 6-speed automatic gearbox and 18.9 kWh battery pack. The vehicle is capable of delivering 30 mile all-electric operation, along with an impressive Utility Factor weighted fuel economy of 50 mpgee. This paper presents the vehicle model development done by the Arizona State University EcoCAR-3 team in year-1 of the competition. The paper explains the detailed vehicle architecture, modeling platform, technical goals of the team and vehicle performance and energy consumption calculations. Control strategies for power flow management, as well as control system development has been addressed, along with approaches used to address any modeling imperfection.

The 3D Thermal modeling utilizes a Finite Differencing heat alteration method augmented with empirical boundary conditions is employed to develop 3D thermal model for the integration of thermoelectric modules with proton exchange membrane fuel cell stack. Hardware-in-Loop was designed under pre-defined drive cycle to obtain fuel cell performance parameters along with anode and cathode gas flow-rates and surface temperatures. The fuel cell model is used to conjugate the experimental boundary conditions with the Finite Differencing code, which implemented heat generation across the stack to depict the chemical composition process. The structural and temporal temperature contours obtained from this model are in compliance with the actual recordings obtained from the infrared detector and thermocouples. The model is harmonized with thermo-electric modules with a modeling strategy, which enables optimize better temporal profile across the stack. This study presents the improvement of a 3D thermal model for proton exchange membrane fuel cell stack along with the interfaced thermo-electric module. The model provided a virtual environment using a model-based design approach to assist the design engineers to manipulate the design correction earlier in the process and eliminate the need for costly and time consuming prototypes.

The aim of this study is to develop a material selection framework structured around a knowledge-based system (KBS). Specifically, a hybrid data mining technique is employed to extract knowledge from large datasets using cluster analysis techniques; the mined knowledge then serves as the inference logic within the KBS designed for material selection purposes. Cluster analysis results are used as a basis for the tree-based structure of the KBS where if–then rules are developed based on the general cluster properties; that is, inference logic is structured in a way such that it can predict general sustainability characteristics of the material as well as its exact mechanical, cost and physical properties. To develop the structure of the KBS, the selection structure employs sustainable material indices. Additionally, the proposed material selection model of the KBS is purposefully composed of material sustainability, functionality and cost indices. The constructed knowledge is then demonstrated for selecting...

The authors propose an eco-material selection approach based on a set of quantifiable measures for developing a sustainability model within the context of an automobile structure or Body-In-White (BIW). As the established sustainability model consists of both quantitative and qualitative factors, the qualitative factors were transformed into numerical values prior to performing the materials selection process, aided by the Preference Selection Index (PSI) and Principal Component Analysis (PCA) decision-making/supporting tools. The uniqueness of this study comes from using PCA as a scoring tool which is benchmarked against another scoring tool (PSI); however, both PSI and PCA avoid the bias that typically arises from assigning weights to different design attributes, as it is not necessary to assign a relative importance scheme between candidate materials. In this study, however, the authors detail the potential of this objective selection scheme to balance the technological, economical, societal and ecological constraints in the design of automobile bodies.

Nowadays life cycle tools namely; Life Cycle Assessment (LCA), Life Cycle Costing (LCC), and Life Cycle Optimization (LCO) are being used to assess new vehicular structures from sustainability and design for the environment perspectives. This manuscript implements a Life Cycle Assessment (LCA) based design approach to assess the performance of vehicular Body-In-White’s (BIW) through its complete life cycle. The proposed LCA model will aid in the early design stages (i.e. conceptual design stage) serving as an eco-design decision-making support tool. This study provides a complete life cycle assessment covering the extraction and the processing of virgin materials, the manufacturing, the use and maintenance stage, the end-of-life stage, in addition to the fuel extraction and production stages. Traditional LCA studies do not usually consider the latter stages which accounts for a significant portion of the energy consumed and the generated CO2 emissions. This study results show that the material selection for vehicular applications is a sensitive process not only to the vehicle lifetime (as expressed in traveled miles), but also to the environmental burdens from the extraction stage and recyclability efforts. Additionally, the proposed study shows the effect of the different materials choices on the vehicle structure functionality.

This manuscript discusses the effect of manipulating the Relative Humidity (RH) along with the Dry Bulb Temperature (DBT) on vehicular cabins’ environment in terms of the overall thermal comfort and human occupants’ thermal sensation. The study uses the Berkeley and the Fanger models to investigate the human comfort through analyzing the (RH) effect from three specific perspectives; firstly its effect on other environmental conditions such as the Dew Point Temperature (DPT), the Enthalpy (H), the vapor pressure (vp) and the humidity ratio (ω) in the cabin. This will be done during the summer and winter periods. Secondly, the cabin local sensation (LS) and comfort (LC) will be analyzed for different body segments mainly; the head, chest, back, hands and feet with the addition of the overall sensation (OS) and the overall comfort (OC). This will be done using a thermal manikin based on the Berkeley model. Thirdly, the human sensation will be measured by the Predicted Mean Value (PMV) and the Predicted Percentage Dissatisfied (PPD) indices during the summer and the winter periods using the Fanger model calculations. From this study and according to the Berkeley model; the RH value should be controlled and synced with the cooling process such that at the early stage (rapid transient) low RH value should be enforced; while a high RH value is needed in the steady state phase. During the start of the heating process (winter conditions), the RH value does not play a major role due to low temperature in the passenger compartment. However, at later periods until the end of the heating process, a low RH value is needed to achieve the needed comfort level. According to Fanger model, in the summer period as the RH value increases, the A/C can achieve the human comfort zone (PMV = ∓0.5) in lesser time than if the RH value is not controlled. While in the winter period, as the RH value decreases, the A/C reaches the human comfort zone faster. So, this study shows that controlling the relative humidity along with (DBT) enables the cabin to reach the comfort zone faster than the sole control of the cabin (DBT), in both the cooling and the heating processes i.e. summer and winter conditions respectively.

SUMMARY Presented study discusses the development of a finite differencing (FD) thermal model for a power-split hybrid configuration employing a nickel-metal hydride battery pack. A resistance–capacitance electro-thermal model is used to couple the experimental boundary conditions (current, voltage, state of charge, and temperature) with the modeled battery resistance to capture its electro-chemical behavior and the cell exothermic reactions. Battery current, voltage, and temperature (discrete and full field) for a vehicle with a power-split hybrid configuration were collected under different standard (Federal Highway Driving Schedule and Federal Urban Dynamometer Driving Schedule (FUDS)) and artificially generated driving cycles. This manuscript analyzes the battery current and voltage in relation to vehicle speed and shows how the proposed FD model predicts the spatial and temporal temperature profiles of the power train in good agreement with the vehicle data as reported by the on-board diagnostics module. Copyright © 2011 John Wiley & Sons, Ltd.

This manuscript discusses the effect of manipulating the Relative Humidity RH of in-cabin environment on the thermal comfort and human occupants’ thermal sensation. The study uses thermodynamic and psychometric analyses, to incorporate the effect of changing RH along with the dry bulb temperature on human comfort. Specifically, the study computes the effect of changing the relative humidity on the amount of heat rejected from the passenger compartment and the effect of relative humidity on occupants comfort zone. A practical system implementation is also discussed in terms of an evaporative cooler design. The results show that changing the RH along with dry bulb temperature inside vehicular cabins can improve the air conditioning efficiency by reducing the heat removed while improving the Human comfort sensations as measured by the Predicted Mean Value PMV and the Predicted Percentage Dissatisfied PPD indices.

This manuscript discusses the development of a 3D thermal model for a power-split hybrid powertrain, including its battery modules and power electronics. The 3D model utilizes a finite differencing (FD) heat transfer algorithm, complemented with experimental boundary conditions. The experimental setup is configured to acquire the battery current, voltage, and its inner and surface temperatures in discrete and in full-field scans. The power-split hybrid configuration is tested using a standard and artificial driving cycles. A battery resistance model is then used to couple the experimental boundary conditions with the finite differencing code, which employed a cell-based internal heat generation model to describe the pack chemical reaction mechanism. This study presents a complete analysis based on battery current and voltage in relation to vehicle speed. The proposed model also predicts the powertrain spatial and temporal temperature profiles in agreement with the vehicle actual conditions as indicated by the On-Board Diagnosis (OBD) module.

This paper presents a new method for the design and validation of advanced propulsion systems using a new approach called vehicle hardware–in–the–loop (VHiL); where the development process, and mainly the validation phase, of adding hybrid electric powertrain modules to an existing platform is carried out faster, in a cost effective and controllable manner. In the VHiL laboratory a complete real vehicle equipped with a conventional powertrain is set up in a hardware–in–the–loop simulation environment, where a chassis dynamometer is used to simulate the road load. The working principle and the added value of VHiL are demonstrated with test results of the performance of the system. This new concept assists validating the inclusion of hybrid electric module to an existing platform during the design/concept stage.