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A Networked Electric Vehicle (NEV) that can convert energy in the vehicle back to the grid when it has excess has the similar electrical characteristics to stationary energy storage devices. A Vehicle-to-Grid (V2G) system, which is composed of these NEVs, can mitigate the impact of renewable penetration, minimize the grid losses and improve the reliability of electricity supply. The goal of the paper is to propose an innovative V2G system with NEVs including mathematical modeling and practical implementation. More importantly, as one approach, the international unified standard IEC 61850 has been integrated into the system, with the aim to standardize the communication network. In the paper, authors investigate the current state of art in the integration of IEC 61850 into power grid systems, introduce a mathematical modeling of NEV that can realize V2G functionality and develop an explicit integration procedure including steps of system architecture, data set design and communication between gateway and client. The results represent a successful implementation of V2G system with the integration of IEC 61850, which implement a power system test bed with providing stable power quality and unified communication network.

In this paper, we propose and implement a smart Electric Vehicle (EV) charging algorithm to control the EV charging infrastructures according to users' price preferences. Charging boxes, equipped with bi-directional communication devices and smart meters, can be remotely monitored by the proposed charging algorithm applied to EV control center and mobile app. On the server side, ARIMA model is utilized to fit historical charging load data and perform day-ahead prediction. A pricing strategy with energy bidding policy is proposed and implemented to generate a charging price list to be broadcasted to EV users through mobile app. On the user side, EV drivers can submit their price preferences and daily travel schedules to negotiate with Control Center to consume the expected energy and minimize charging cost simultaneously. The proposed algorithm is tested and validated through the experimental implementations in UCLA parking lots.

A two-dimensional (2D) graphics hierarchical representation framework and an on-demand content delivery mechanism for facilitating mobile engineering collaboration are presented in this paper. Multi-level graphics content sub-division is utilized to transform large engineering graphics into multiple levels of Scalable Vector Graphics (SVG) content. The hierarchical structure of the SVG content that maintains the relationship between the sub-divided content is formed during the process of sub-division. The divided content is selectively delivered and rendered on the mobile devices in an on-demand fashion. A prototypical system of the proposed approach is implemented and the performance of the framework is evaluated.

Product assembly design is a complex activity involving collaboration between several designers. Currently, many manufacturing firms out source the design and development of different portions of a product to different suppliers. Due to the absence of an integrated tool for collaborative product assembly design, designers currently follow an indirect approach. This makes collaboration an unorganized and inefficient activity. This paper discusses the architectural novelties and design considerations utilized to develop an integrated collaborative assembly design tool. Further, the scenarios of using such a tool are discussed in detail. This discussion highlights how the tool contributes towards making collaboration an organized and efficient activity and enables designers to rapidly design and prototype the product assembly.

Chi-Cheng Chu, Jianzhong Mo, and Rajit Gadh ABSTRACT In this paper, a series of interface tests on interaction approach for the generation of geometric shape designs via multi-sensory user interface of a Virtual Reality (VR) based System is presented. The goal of these interface tests is to identify an effective user interface for VR based Computer-Aided Design (CAD) system. The intuitiveness of the VR based interaction approach arises from the use of natural hand movements/gestures, and voice commands that emulate the way in which human beings discuss geometric shapes in reality. In order to evaluate the proposed interaction approach, a prototypical VR-CAD system is implemented. A series of interface tests were performed on the prototypical systems to determine the relative efficiency of a set of potential interaction approach with respect to specific fundamental design tasks. The interface test and its results are presented in this paper.

This paper analyzes the problem of global disassembly of a selected component from a geometrically constrained assembly. The geometric constraints are: (i) spatial constraints due to the three-dimensional geometric interactions between the components in an assembly; and (ii) user-defined constraints, such as grouping of components as subassemblies and directional constraints on component geometry. A new algorithm has been proposed to determine a non-interfering disassembly sequence for a selected component, minimizing the number of simultaneous component removals. The algorithm analyzes both the spatial constraints of the assembly geometry and the user-defined constraints in evaluating the accessibility of components, which is followed by determining the topological disassembly ordering of the components to evaluate an optimal sequence. Preliminary implementation results of the algorithm for a geometrically constrained assembly are presented.

A microgrid can be characterized by its integration of distributed energy resources and controllable loads. Such integration brings unique challenges to the microgrid management and control which can be significantly different from conventional power systems. Therefore, a conventional energy management system (EMS) needs to be re-designed with consideration of the unique characteristics of microgrids. To this end, we propose a microgrid EMS named a microgrid platform (MP). We take into account all the functional requirements of a microgrid EMS (i.e., forecast, optimization, data analysis, and human-machine interface) and address the engineering challenges (i.e., flexibility, extensibility, and interoperability) in the design and development of the MP. Moreover, we deploy the prototype system and conduct experiments to evaluate the microgrid management and control in real-world settings at the UCLA Smart Grid Energy Research Center. Our experimental results demonstrate that the MP is able to manage various devices in the testbed, interact with the external systems, and perform optimal energy scheduling and demand response.

In this paper, five imputation methods namely Constant (zero), Mean, Median, Maximum Likelihood, and Multiple Imputation methods have been applied to compensate for missing values in Electric Vehicle (EV) charging data. The outcome of each of these methods have been used as the input to a prediction algorithm to forecast the EV load in the next 24 hours at each individual outlet. The data is real world data at the outlet level from the UCLA campus parking lots. Given the sparsity of the data, both Median and Constant (=zero) imputations improved the prediction results. Since in most missing value cases in our database, all values of that instance are missing, the multivariate imputation methods did not improve the results significantly compared to univariate approaches.

Three algorithms for the forecasting of energy consumption at individual EV charging outlets have been applied to real world data from the UCLA campus. Out of these three algorithms, namely k-Nearest Neighbor (kNN), ARIMA, and Pattern Sequence Forecasting (PSF), kNN with k=1, was the best and PSF was the worst performing algorithm with respect to the SMAPE measure. The advantage of PSF is its increased robustness to noise by substituting the real valued time series with an integer valued one, and the advantage of NN is having the least SMAPE for our data. We propose a Modified PSF algorithm (MPSF) which is a combination of PSF and NN; it could be interpreted as NN on integer valued data or as PSF with considering only the most recent neighbor to produce the output. Some other shortcomings of PSF are also addressed in the MPSF. Results show that MPSF has improved the forecast performance.

Integration of Electrical Vehicles (EVs) with power grid not only brings new challenges for load management, but also opportunities for distributed storage and generation in distribution network. With the introduction of Vehicle-to-Home (V2H) and Vehicle-to-Grid (V2G), EVs can help stabilize the operation of power grid. This paper proposed and implemented a hybrid V2H/V2G system with commercialized EVs, which is able to support both islanded AC/DC load and the power grid with one single platform. Standard industrial communication protocols are implemented for a seamless respond to remote Demand Respond (DR) signals. Simulation and implementation are carried out to validate the proposed design. Simulation and implementation results showed that the hybrid system is capable of support critical islanded DC/AC load and quickly respond to the remote DR signal for V2G within 1.5kW of power range.

Energy management in microgrids is typically formulated as a non-linear optimization problem. Solving it in a centralized manner not only requires high computational capabilities at the microgrid central controller (MGCC) but may also infringe customer privacy. Existing distributed approaches, on the other hand, assume that all the generations and loads are connected to one bus and ignore the underlying power distribution network and the associated power flows and system operational constraints. Consequently, the schedules produced by those algorithms may violate those constraints and thus are not feasible in practice. Therefore, the focus of this paper is on the design of a distributed energy management strategy (EMS) for the optimal operation of microgrids with consideration of the distribution network and the associated constraints. Specifically, we formulate microgrid energy management as an optimal power flow problem and propose a distributed EMS where the MGCC and the local controllers jointly compute an optimal schedule. As one demonstration, we apply the proposed distributed EMS to a real microgrid in Guangdong Province, China consisting of photovoltaics, wind turbines, diesel generators, and a battery energy storage system. The simulation results demonstrate that the proposed distributed EMS is effective in both islanded and grid-connected mode. It is also shown that the proposed algorithm converges fast.

Integration of Electrical Vehicles (EVs) with power grid not only brings new challenges for load management, but also opportunities for distributed storage and generation. This paper comprehensively models and analyzes distributed Vehicle-to-Grid (V2G) for automatic load sharing with driver preference. In a micro-grid with limited communications, V2G EVs need to decide load sharing based on their own power and voltage profile. A droop based controller taking into account driver preference is proposed in this paper to address the distributed control of EVs. Simulations are designed for three fundamental V2G automatic load sharing scenarios that include all system dynamics of such applications. Simulation results demonstrate that active power sharing is achieved proportionally among V2G EVs with consideration of driver preference. In additional, the results also verify the system stability and reactive power sharing analysis in system modelling, which sheds light on large scale V2G automatic load sharing in more complicated cases.

This paper describes the core cellphone application algorithm which has been implemented for the prediction of energy consumption at Electric Vehicle (EV) Charging Stations at UCLA. For this interactive user application, the total time of accessing database, processing the data and making the prediction, needs to be within a few seconds. We analyze four relatively fast Machine Learning based time series prediction algorithms for our prediction engine: Historical Average, k-Nearest Neighbor, Weighted k-Nearest Neighbor, and Lazy Learning. The Nearest Neighbor algorithm (k Nearest Neighbor with k=1) shows better performance and is selected to be the prediction algorithm implemented for the cellphone application. Two applications have been designed on top of the prediction algorithm: one predicts the expected available energy at the station and the other one predicts the expected charging finishing time. The total time, including accessing the database, data processing, and prediction is about one second for both applications.

A Distributed Energy Resources (DER) system, composed of distributed generation and storage units, has been proposed as a promising enhancement to the traditional power grids. One key challenge to implement a DER system, however, places on standardizing the communication network for seamless information exchange. As one approach, this paper focuses on integrating IEC 61850, which is an international unified standard for standardizing the communication network within a substation, into a DER system, using the UCLA SMERC building as test bed. To this end, we discuss a mathematical model of PV generation, present a representative demand profile, and develop a battery charging/discharging control algorithm. Moreover, we demonstrate a procedure to integrate IEC 61850 into the DER system step by step, with configuring the communication network and defining the data structure for the information exchange.

This paper contains a control scheme for power sharing in islanded microgrids with inverter-sourced distributed energy resources that combines robust control and droop control. As the load within the microgrid changes, the inverter-sourced generators will share this change in load. This paper includes a background on control schemes for power sharing and highlights the difficulty in exact reactive power sharing. In this paper a Distributed Energy Resource (DER) unit consists of an energy source and an energy storage system. A robust control scheme is proposed for the energy source which is augmented by droop control for the storage system. The performance of the proposed controller is demonstrated using a test microgrid system.

In this paper, we develop a general framework of distributed access control which allows for anytime connections and disconnections of volatile renewable energy resources in the power grid. We formally prove that the hard state constraints are satisfied all the time and the asymptotic stability is reached if connections and disconnections only happen for a finite number of times. Our framework and analysis leverage the tools of input-to-state stability and small gain theorems in nonlinear systems. The performance of our framework is illustrated by a case study on frequency control with wind integration.

WINSmartEV™ is a smart electric vehicle charging system that has been built and is currently in operation. It is a software and network based EV charging system designed and built around the ideas of intelligent charge scheduling, multiplexing (connecting multiple vehicles to each circuit) and flexibility. This paper gives an overview of this smart charging system with an eye toward its unique features and capabilities.

With an increased number of plug-in electric vehicles (PEVs) on the roads, PEV charging infrastructure is gaining an ever-more important role in simultaneously meeting the needs of drivers and those of the local distribution grid. However, the current approach to charging is not well suited to scaling with the PEV market. If PEV adoption continues, charging infrastructure will have to overcome its current shortcomings such as unresponsiveness to grid constraints, low degree of autonomy, and high cost, in order to provide a seamless and configurable interface from the vehicle to the power grid. Among the tasks a charging station will have to accomplish will be PEV identification, charging authorization, dynamic monitoring, and charge control. These will have to be done with a minimum of involvement at a maximum of convenience for a user. The system proposed in this work allows charging stations to become more responsive to grid constraints and gain a degree of networked autonomy by automatically identifying and authorizing vehicles, along with monitoring and controlling all charging activities via an RFID mesh network consisting of charging stations and in-vehicle devices. The proposed system uses a ZigBee mesh network of in-vehicle monitoring devices which simultaneously serve as active RFID tags and remote sensors. The system outlined lays the groundwork for intelligent charge-scheduling by providing access to vehicle’s State of Charge (SOC) data as well as vehicle/driver IDs, allowing a custom charging schedule to be generated for a particular driver and PEV. The approach presented would allow PEV charging to be conducted effectively while observing grid constraints and meeting the needs of PEV drivers.

With the rapid development of wind turbine, photovoltaicand battery technologies, renewable energy resources such as wind and solar become the most common distributedgenerations (DG) that are being integrated into microgrids. One key impediment is to determine the sizes and placements of DGs within which the microgrid can achieve its maximum potential benefits. The objective of the paper is to study and propose an approach to find the optimal sizes and placements of DGs in a microgrid. The authors propose a comprehensive objective function with practical constraints which take all the important factors that will impact the reliability of the power grid into account. To solve the optimization problem, genetic algorithm (GA) is used and compared with a mathematical optimization method nonlinear programming. The proposed model is tested on a real microgrid, i.e. Jeju Island, to evaluate and validate the performances of the approach. The simulation results present the optimal configuration of DGs for Jeju Island power grid. The analysis on results shows that GA maintains a delicate balance between performance and complexity. It is concluded that GA performs better not only in accuracy, stability, but also in computation time.

Typically, during product design collaborating, designers share design data and assembly models. However, due to the limited bandwidth of the Internet transfer of detailed CAD based assembly models is slow. Therefore, tools based on polygonized representations of assembly models have been utilized during collaborative design. These models are primarily used for visualization, which is an important activity during modeling. However, providing the designers with the ability to perform real-time geometric modification, assembly constraints specification and concurrent design of different components/sub-assemblies will enable designers to collaborate effectively during design. This paper presents a new geometric representation called the AREP and a prototypical system (cPAD) that uses this representation, which implements the collaboration paradigm by supporting these activities.

Considerable progress has been made on automatic hexahedral mesh generation in recent years. A few automated meshing algorithms (e.g. mapping, submapping, sweeping) have proven to be very reliable on certain classes of geometry. While it is always worth pursuing general algorithms viable on arbitrary geometry, a combination of the well-established algorithms is ready to take on classes of complicated geometry. By partitioning the entire geometry into meshable pieces matched with appropriate meshing algorithms, the original geometry becomes meshable and may achieve better mesh quality. Each meshable portion is recognized as a meshing feature. This paper, which is a part of the feature based meshing methodology, presents the work on shape recognition and volume decomposition to automatically decompose a CAD model into hex meshable volumes. There are four phases in this approach: Feature Determination to extract decomposition features; Cutting Surfaces Generation to form the cutting surfaces; Body Decomposition to get the imprinted volumes; and Meshing Algorithm Assignment to match volumes decomposed with appropriate meshing algorithms. This paper focuses on describing feature determination and volume decomposition; the last part has been described in another paper. The feature determination procedure is based on the CLoop feature recognition algorithm that is extended to be more general. Some decomposition and meshing results are demonstrated in the final section.

Virtual reality applications are making valuable contributions to the field of product realization. This paper presents an assessment of the hardware and software capabilities of VR technology needed to support a meaningful integration of VR applications in the product life cycle analysis. Several examples of VR applications for the various stages of the product life cycle engineering are presented as case studies. These case studies describe research results, fielded systems, technical issues, and implementation issues in the areas of virtual design, virtual manufacturing, virtual assembly, engineering analysis, visualization of analysis results, and collaborative virtual environments. Current issues and problems related to the creation, use, and implementation of virtual environments for engineering design, analysis, and manufacturing are also discussed. @DOI: 10.1115/1.1353846#

This paper analyzes the problem of disassembling multiple selected components from an assembly, defined as selective disassembly, and presents algorithms for efficient disassembly analysis of geometric models. Applications for selective disassembly include assembling, maintenance and recycling. A new approach called ‘Disassembly Wave Propagation’ is proposed to determine a selective disassembly sequence with minimal component removals from an assembly. This approach defines: (i) disassembly waves to topologically arrange the components denoting the disassembly order and (ii) intersection events between the waves to determine the selective disassembly sequences. In order to evaluate a minimal removal sequence in a feasible computation time, algorithms are proposed that prioritize and process the intersection events based on the order in which they occurred. The proposed algorithms analyze selective disassembly from the geometric perspective and are applicable for both two-dimensional and three-dimensional product assemblies. [S1050-0472(00)01402-1]

Determining whether an assembly can be constructed from its components at the design stage potentially reduces downstream assembly problems. This determination can be accomplished by performing a disassembly analysis of the assembly′s geometric model. This paper presents two abstractions derived from the assembly′s geometric model that can determine the validity of the assembly: (1) the Assembly Topology Graph (ATG); and (2) the set of boundary components. The first abstraction, the ATG, is a graph whose nodes represent the components in the assembly and whose edges represent a non-null intersection of the convex hulls of component pairs. The second abstraction, the set of boundary components, represents components that intersect the boundary (or convex hull) of the assembly. These boundary components are typically the ones most accessible with respect to disassembly. This paper also discusses an algorithm, which utilizes the ATG to determine pair-wise interlocking components. If such component pairs are absent, then the disassembly sequence for the removal of components in the assembly is determined by analyzing the set of boundary components for disassembly. This procedure is repeated until all the components in the assembly are disassembled (for a valid assembly).

Selective disassembly involves separating a selected set of components from an assembly. Applications for selective disassembly include de-manufacturing (maintenance and recycling), and assembling. This paper presents a new methodology for performing design for selective disassembly analysis on the CAD model of an assembly. The methodology involves the following three steps: (i) identifying the components to be selectively disassembled for de-manufacturing by a software program or designer, (ii) determining an optimal (e.g. minimal cost) disassembly sequence for the selected components that involves a computationally efficient two-level reduction procedure: (a) the determination of a set of sequences with an objective of minimal component removals via a wave propagation approach that topologically order components in an assembly for selective disassembly, and (b) the evaluation of resulting sequences based on an objective function (e.g. minimal cost) to identify an optimal sequence, and (iii) Performing disassembly design decisions based on the evaluated optimal sequence. Preliminary implementation results of the selective disassembly methodology in sequencing and disassembly cost evaluation, and application of the selective disassembly technique for de-manufacturing assessment are presented.

The current paper presents a pseudo-sweep algorithm to determine whether a given volume constitutes an approximately swept shape for the purpose of hexahedral finite element mesh generation. The pseudo-swept shape determination approach consists of three steps. Step 1: Determining the source surface, target surface, and lateral surface of a given solid object B. Two requirements: topological and geometric requirements, are used to determine these three surfaces. Step 2: Creating a submappable lateral surface. A submappable surface is one that allows the sweeping of a two dimensional quadrilateral mesh from the source surface to target surface. Step 3: Modifying the topology of the source surface. If the topologies of the source and target surfaces are different, an approach called Topology Mapping is applied. The Topology Mapping approach maps the target surface to the source surface so that sweeping of quadrilateral mesh from the source surface to the target surface is possible. Once the above three steps are applied, a hexahedral mesh is generated by sweeping a quadrilateral mesh from the source surface, along the lateral surface, to the target surface.

Our society expects engineers to develop products that are affordable, functional and sustainable. Effective product realization methods and tools are the answers to these societal expectations. In this paper, a new type of CAE tools, called virtual and augmented reality technologies, is introduced, reviewed and examined to reveal their great potentials in product realization. Specific areas where these emerging technologies can make a big difference are highlighted to illustrate the possible new paradigms of product realization. Subjects that require continuing R&D efforts to mature the technologies for real-world engineering applications are also identified. Both product development engineers and virtual reality researchers should find this paper valuable to guide their efforts in developing a common road map for joint explorations. It is anticipated that the results from these joint explorations will enable engineers to deliver new products to the society across the time, space and other boundaries with high efficiency and great ease in the future.

The design paradigm called virtual prototyping (VP) is important because of the need to manufacture products in a short period of time and in a cost effective manner. By replacing the building of physical prototypes for testing various design issues such as usability, life-cycle analysis, functionality and so on with so called “virtual models” on a computer and analyzing them, virtual prototyping is achieved. One of the design issues that has become increasingly important is the “design-for-disassembly (DFD)” paradigm. A well designed product that is easy to disassemble has the obvious advantages when it needs to be taken apart for service or end-of-life recycling. Therefore a design tool that can tie the DFD issues into a virtual prototyping system is of considerable interest. This paper attempts to address this particular issue in the virtual prototyping area: DFD as applied to VP. This paper presents an overview of a detailed DFD method. An algorithm that can be readily tied into a computer aided desig...

Disassembling a selected component from an assembly, defined as selective disassembly, is important for applications such as maintenance, recycling and reuse. This paper presents a geometric algorithm to solve the following selective disassembly problem: given an assembly and a selected component to be disassembled, determine the disassembly sequence with minimum component removals (motions), defined as an optimum sequence. We propose an abstraction “wave propagation” that analyzes the assembly from the selected component outwards, and orders the components for selective disassembly. The main contributions of this research are: (1) determining an optimal disassembly sequence; (2) reducing the search space by analyzing a subset of components in the assembly; and (3) providing a polynomial average complexity algorithm. The proposed selective disassembly approach applies to both two dimensional and three-dimensional assemblies.

Virtual prototyping (VP) typically involves analyzing computer aided design (CAD) models for different end applications such as manufacturability or assemblability analysis. Such analyses may be performed via the aid of expert system agents which could be residing in a distributed fashion on the Internet. Each expert system agent/module requires CAD information at a certain level of geometric abstraction and outputs the analysis at a different level of abstraction. Therefore, a basis is needed to define these different levels of geometric abstraction. The current paper defines and analyzes these different levels of geometric abstraction in the context of an architecture for achieving VP via a central broker that interacts with these different modules—each providing a different level of abstraction.

This paper presents the implementation of the algorithms used to compute the die-open directions for a near-net-shape manufac tured part described in "Virtual Prototyping of Die Design Part One. Theory and Formulation." In this approach, a set of concavity features is used to determine the die-open directions for a given part by first determining the convex hull of the geometry and then by performing a boolean subtraction between the convex hull of the part and the three-dimensional solid model of the original part geometry. This will pro vide the set of concavity features that restrict the possible die-open directions for the part. A set of possible die-open directions is deter mined for each concavity feature. The set of directions common to all concavity features is then determined to be the set of die-open direc tions for the part. The convex hull of a part (which is a convex part) has unrestricted draw, implying that a convex part can be oriented in any fashion inside a die. The algorithms for this approach, its computational analysis, and strengths and weaknesses of the implementation are discussed in this paper.

In this thesis, a human-computer interaction approach for the generation of geometric shapes via multi-sensory user interface of a Virtual Reality (VR) based System is presented. Through the use of VR devices, geometric design can be more effectively inputted into the Computer-Aided Design (CAD) system in a natural and physically intuitive way. The focus of this research is on determining a set of efficient interaction approach by using the combinations of auditory, tactile, and visual sensory modalities to accomplish typical CAD tasks. In order to evaluate the efficiency of the proposed interaction approaches, prototypical VR-CAD systems are implemented as part of this research. A series of interface tests were performed on the prototypical systems to determine the relative efficiency of the interaction approaches. Interface test results indicate that auditory input, voice commands, are effective in operation activations such as rotating viewpoint, creating/deleting entities in the virtual environment. The tactile input, hand actions/motions, are found to be highly efficient for navigation, entity selection, complex 3D manipulations of entities and dynamically changing entity's dimension in the VR-CAD system. It is also determined that building simple geometry shapes containing canonical forms, such as blocks, cylinders, spheres, etc, using VR interface results in a speedup of 1.5 to 2.0 times over the traditional interface. For more complex shapes, the speedup factor is about 3 to 4 times. This indicates that there are greater benefits when designing complex geometry shapes than design simpler shapes in a VR CAD system. The contribution of this research lies on setting a new paradigm for multi-sensory input output interaction approaches of a VR based CAD system to provide an easy-to-use and effective tool for product shape design.

This paper describes an approach for creating concept shape designs in a virtual reality environment— covirds (COnceptual VIRtual Design System). Concept design refers to the ab initio design of a product or part. In concept design, the product details such as shape features and exact dimensions are not rigidly defined and the designer has some freedom in determining the shape and dimensions of the product. Current cad require the designer to specify shape and dimensions to create cad models of products even though these are probably not necessary at the concept development stage. covirds overcomes these drawbacks by providing a bi-modal voice and hand-tracking based user interface to the VR-based cad modeling environment. This interface allows rapid concept design creation without requiring time consuming shape description and the tedious specifications of exact dimensions.

In near-net-shape manufacturing processes, an important phase of die design is the determination of die-open directions that allow a part to be successfully ejected from a die. Current research shows that possible die-open directions can be derived directly from the geometric information of a part, and that the ejectability of a part is restricted only by its concavity features. The approach to die-open direction determination described in this paper is applicable when a concavity feature has one of the following characteristics: (1) it is created by the intersection of one or several non-parallel extrusions along a straight line; or (2) it is created by the rotation of two-dimensional cross-sections. A cross-sectional plane may be used to separate the elements of the concavity feature, thereby making a transition into two-dimensional space. Within this two-dimensional space, the known principles of die-open direction determination are applied, resulting in a two-dimensional set of possible die-open directions. The two-dimensional results can then be expanded back into the three-dimensional space according to the known creation characteristics of the concavity feature. This procedure is applicable for concavity features that are blind concavities (i.e. not through-holes). The die-open direction determination of through-holes is performed on the complementing solid of the through-hole. This complementing solid's set of die-open directions is then transformed back to the set of die-open directions for the given through hole.

Product reuse or recyclability is enhanced by designing the product for inexpensive and efficient disassembly. However, accomplishing enhanced product design requires design for disassembly (DFD) tools. This paper presents a disassembly framework that consists of design modules; both of these are embodied in the geometric DFD tool. These modules consist of different tasks including: selection of the appropriate disassembly method; producing an optimized disassembly sequence; evaluating a disassembly sequence for cost; producing design change recommendations. These considerations make a product easier to disassemble and therefore have potential benefit to the environment.

Smart charging infrastructure is required to meet the growing demand for Electrical Vehicle (EV) charging from ever more abundant EV owners. WINSmartEV™ is a software based smart charging infrastructure that can monitor, control and manage EV charging. It also can use multiplexing to share scarce charging resources among different EVs plugged in simultaneously. By default WINSmartEV™ uses a round-robin algorithm to schedule charging time between EVs charging on the 120V level one charging device. In order to enhance user acceptance of this technology, charge time allocation fairness is defined and an algorithm to enhance this fairness is proposed.

Plug-In Electric Vehicle (PEV) charging today happens with little knowledge of the state of the vehicle being charged. In order to implement smart charging algorithms and other capabilities of the future smart grid, provisions for remote PEV monitoring will have to be developed and tested. The UCLA Smart-grid Energy Research Center (SMERC) is working on a smart charging research platform that includes data acquired in real time from PEVs being charged in order to investigate smart charging algorithms and demand response (DR) strategies for PEVs in large parking garage settings. The system outlined in this work allows PEVs to be remotely monitored throughout the charging process by a smart-charging controller communicating through a mesh network of charging stations and in-vehicle monitoring devices. The approach may be used for Vehicle to Grid (V2G) communication as well as PEV monitoring.

As Electric Vehicles (EVs) increase, charging infrastructure becomes more important. When during the day there is a power shortage, the charging infrastructure should have the options to either shut off the power to the charging stations or to lower the power to the EVs in order to satisfy the needs of the grid. This paper proposes a design for a smart charging infrastructure capable of providing power to several EVs from one circuit by multiplexing power and providing charge control and safety systems to prevent electric shock. The safety design is implemented in different levels that include both the server and the smart charging stations. With this smart charging infrastructure, the shortage of energy in a local grid could be solved by our EV charging management system.

With an increased number of Electric Vehicles (EVs) on the roads, charging infrastructure is gaining an ever-more important role in simultaneously meeting the needs of the local distribution grid and of EV users. This paper proposes a mesh network RFID system for user identification and charging authorization as part of a smart charging infrastructure providing charge monitoring and control. The Zigbee-based mesh network RFID provides a cost-efficient solution to identify and authorize vehicles for charging and would allow EV charging to be conducted effectively while observing grid constraints and meeting the needs of EV drivers.

Virtual reality is an exciting new field, which may offer significant improvements in the efficiency of human-computer interface for a wide variety of computer applications. This paper serves to identify technology developments in virtual reality hardware devices that may allow for development of a more efficient user interface for computer-aided design packages for mechanical design functions. Presented is a survey of the current state of the art in the rapidly changing field of virtual reality hardware devices. The devices are broken down into classes that are related to user interface features that may improve the efficiency of computer-aided design functions. Classes of virtual reality hardware devices are identified needing future research and development to implement the most effective virtual reality computer-aided design interface.

The current research presents a feature-based approach to minimize the number of set-ups in the machining process planning system. It analyses machining features with a set of knowledge-based rules to determine the machining process plan for a part. In this approach, features are classified according to the number of possible tool approach directions that can be used to machine them. This divides features into two classes: single tool approach direction (STAD) features and multiple tool approach direction (MTAD) features. The process planning system groups all the STAD features with the same tool approach directions into one set-up. MTAD features are integrated, if possible, into these set-ups by choosing the appropriate tool approach direction for each MTAD feature. If this is not possible, a new set-up is created. This minimizes the total number of set-ups for machining the part. Knowledge-based rules are applied to guide the search for proper ordering between machining processes and set-ups of a part. Subsequently, a machining process plan with a minimized number of set-ups is created. The process planning system that uses this approach can serve as an integral part of a feature-based product and process design system.

A microgrid is characterized by the integration of distributed energy resources and controllable loads in a power distribution network. Such integration introduces new, unique challenges to microgrid management that have never been exposed to traditional power systems. To accommodate these challenges, it is necessary to redesign a conventional Energy Management System (EMS) so that it can cope with intrinsic characteristics of microgrids. While many projects have shown excellent research outcomes, they have either tackled portions of the characteristics or validated their EMSs only via simulations. This paper proposes a Microgrid Platform (MP), an advanced EMS for efficient microgrid operations. We design the MP by taking into consideration (i) all the functional requirements of a microgrid EMS (i.e., optimization, forecast, human–machine interface, and data analysis) and (ii) engineering challenges (i.e., interoperability, extensibility, and flexibility). Moreover, a prototype system is developed and deployed in two smart grid testbeds: UCLA Smart Grid Energy Research Center and Korea Institute of Energy Research. We then conduct experiments to verify the feasibility of the MP design in real-world settings. Our testbeds and experiments demonstrate that the MP is able to communicate with various energy devices and to perform an energy management task efficiently.

The current paper discusses a fundamentally new approach to defining and finding interactions in computer-aided design (CAD) forms or features. Feature classes are defined using a high-level abstract entity called a loop. Loops define features in a general manner and aid in the definition of feature boundaries as well. Interactions between features exist due to interactions between their boundaries. Several types of interactions are defined and automatically determined from the boundary representation solid model of the part subsequent to performing feature extraction.

The randomness of user behaviors plays a significant role in electric vehicle (EV) scheduling problems, especially when the power supply for EV supply equipment (EVSE) is limited. Existing EV scheduling methods do not consider this limitation and assume charging session parameters, such as stay duration and energy demand values, are perfectly known, which is not realistic in practice. In this paper, based on real-world implementations of networked EVSEs on University of California at Los Angeles campus, we developed a predictive scheduling framework, including a predictive control paradigm and a kernel-based session parameter estimator. Specifically, the scheduling service periodically computes for cost-efficient solutions, considering the predicted session parameters, by the adaptive kernel-based estimator with improved estimation accuracies. We also consider the power sharing strategy of existing EVSEs and formulate the virtual load constraint to handle the future EV arrivals with unexpected energy demand. To validate the proposed framework, 20-fold cross validation is performed on the historical dataset of charging behaviors for over one-year period. The simulation results demonstrate that average unit energy cost per kWh can be reduced by 29.42% with the proposed scheduling framework and 66.71% by further integrating solar generations with the given capacity, after the initial infrastructure investment. The effectiveness of kernel-based estimator, virtual load constraint, and event-based control scheme are also discussed in detail.

A web-based architecture of an radio frequency identification (RFID) tracking solution is proposed and deployed. The architecture attempts to depart from the typical localized approach of most RFID middlewares. The middleware has been replaced by a web service residing in a cloud. The traditional roles of the middleware such as tag data filtering, sorting, storage, and event processing have been redistributed amongst an RFID reader-based application and the web service. This architecture provides more flexibility and control to large scale RFID-based supply chain operations which are global in nature and unsuitable to the traditional localized middleware-based architecture of RFID tracking solutions. The feasibility of the web-based architecture is further augmented by validating performance parameters such as tag processing and primitive and complex event processing delay. Different subarchitectures are also proposed based on performance data for different scales of operations.

The goal of this article is to investigate and research solar generation forecasting in a laboratory-level micro-grid, using the UCLA Smart Grid Energy Research Center (SMERC) as the test platform. The article presents an overview of the existing solar forecasting models and provides an evaluation of various solar forecasting providers. The auto-regressive moving average (ARMA) model and the persistence model are used to predict the future solar generation within the vicinity of UCLA. In the forecasting procedures, the historical solar radiation data originates from SolarAnywhere. System Advisor Model (SAM) is applied to obtain the historical solar generation data, with inputting the data from SolarAnywhere. In order to validate the solar forecasting models, simulations in the System Identification Toolbox, Matlab platform are performed. The forecasting results with error analysis indicate that the ARMA model excels at short and medium term solar forecasting, whereas the persistence model performs well only under very short duration.