Namwoo Kang

Integrated Decision Making in Electric Vehicle and Charging Station Location Network Design

A major barrier in consumer adoption of electric vehicles (EVs) is “range anxiety,” the concern that the vehicle will run out of power at an inopportune time. Range anxiety is caused by the current relatively low electric-only operational range and sparse public charging station (CS) infrastructure. Range anxiety may be significantly mitigated if EV manufacturers and CS operators work in partnership using a cooperative business model to balance EV performance and CS coverage. This model is in contrast to a sequential decision-making model where manufacturers bring new EVs to the market first and CS operators decide on CS deployment given EV specifications and market demand. This paper proposes an integrated decision-making framework to assess profitability of a cooperative business model using a multidisciplinary optimization model that combines marketing, engineering, and operations considerations. This model is demonstrated in a case study involving battery EV design and direct current (DC) fast-CS location network in Southeast Michigan. The expected benefits can motive both government and private enterprise actions. [DOI: 10.1115/1.4029894]

Decomposition-Based Design Optimization of Hybrid Electric Powertrain Architectures: Simultaneous Configuration and Sizing Design

Effective electrification of automotive vehicles requires designing the powertrain’s configuration along with sizing its components for a particular vehicle type. Employing planetary gear systems in hybrid electric vehicle powertrain architectures allows various architecture alternatives to be explored, including singlemode architectures that are based on a fixed configuration and multi-mode architectures that allow switching power flow configuration during vehicle operation. Previous studies have addressed the configuration and sizing problems separately. However, the two problems are coupled and must be optimized together to achieve system optimality. An all-in-one system solution approach to the combined problem is not viable due to the high complexity of the resulting optimization problem. In this paper we propose a partitioning and coordination strategy based on Analytical Target Cascading for simultaneous design of powertrain configuration and sizing for given vehicle applications. The capability of the proposed design framework is demonstrated by designing powertrains with one and two planetary gears for a mid-size passenger vehicle.

An integrated design approach for evaluating the effectiveness and cost of a fleet

This work presents a new method for designing and evaluating different fleet paradigms to determine an effective and cost efficient solution. The method requires the user to define a set of functions which must be carried out by the fleet, as well as a set of candidate vehicles or systems that can carry out these functions. These function and fleet models are then evaluated to determine their performance. All the data is then fed into a stochastic dynamic fleet operation model to identify the amount of vehicles or systems needed to complete each mission defined on a fixed time horizon. The output of the fleet operation model is then used by cost models to determine the cost of completing each fleet mission. The overall approach is demonstrated on a military fleet composed of two different types of vehicle: a conventional fleet and a fleet composed of modules. The method shows the potential for savings using a modular fleet for a hypothetical fleet mission profile; more work in this area is suggested.

Decomposition-based design optimization of hybrid electric powertrain architectures: Simultaneous configuration and sizing design

Effective electrification of automotive vehicles requires designing the powertrain’s configuration along with sizing its components for a particular vehicle type. Employing planetary gear systems in hybrid electric vehicle powertrain architectures allows various architecture alternatives to be explored, including single-mode architectures that are based on a fixed configuration and multi-mode architectures that allow switching power flow configuration during vehicle operation. Previous studies have addressed the configuration and sizing problems separately. However, the two problems are coupled and must be optimized together to achieve system optimality. An all-in-one system solution approach to the combined problem is not viable due to the high complexity of the resulting optimization problem. In this paper we propose a partitioning and coordination strategy based on Analytical Target Cascading for simultaneous design of powertrain configuration and sizing for given vehicle applications. The capability of the proposed design framework is demonstrated by designing powertrains with one and two planetary gears for a mid-size passenger vehicle.Copyright

Autonomous Electric Vehicle Sharing System Design

Car-sharing services promise “green” transportation systems. Two vehicle technologies offer marketable, sustainable sharing: Autonomous vehicles eliminate customer requirements for car pick-up and return, and battery electric vehicles entail zero-emissions. Designing an Autonomous Electric Vehicle (AEV) fleet must account for the relationships among fleet operations, charging station operations, electric powertrain performance, and consumer demand. This paper presents a system design optimization framework integrating four sub-system problems: Fleet size and assignment schedule; number and locations of charging stations; vehicle powertrain requirements; and service fees. A case study for an autonomous fleet operating in Ann Arbor, Michigan, is used to examine AEV sharing system profitability and feasibility for a variety of market scenarios.Copyright

Integrated decision making in electric vehicle and charging station location network design

A major barrier in consumer adoption of electric vehicles (EVs) is ‘range anxiety,’ the concern that the vehicle will run out of power at an inopportune time. Range anxiety is caused by the current relatively low electric-only operational range and sparse public charging station infrastructure. Range anxiety may be significantly mitigated if EV manufacturers and charging station operators work in partnership using a cooperative business model to balance EV performance and charging station coverage. This model is in contrast to a sequential decision making model where manufacturers bring new EVs to the market first and charging station operators decide on charging station deployment given EV specifications and market demand. This paper proposes an integrated decision making framework to assess profitability of a cooperative business models based on a multi-disciplinary optimization model that combines marketing, engineering, and operations. This model is demonstrated in a case study involving battery electric vehicle design and direct-current fast charging station location network in the State of Michigan. The expected benefits can motive both government and private enterprise actions.© 2014 ASME

A Sense of Dichotomy in Household Space and Smartphone

In this paper, we apply dichotomous aspects discussed in architectural theories to electronic devices and explore the relationship. In order to investigate the similarities and the differences between how people’s attitudes change for the sense of individuality-communality and private-public in a household environment and in a product environment as the level of depth increases, we designed an experiment with a scenario that guides subjects to explore through a household space virtually displayed on a large display as well as a smartphone space on an actual phone. At the end of every task, we asked the subjects to complete a semantic differential survey designed using the terms used in architecture that relate to both social and spatial dichotomies. From this experiment, we can suggest that the use of analogy between the two environments is appropriate especially as the depth of navigation increases such as going into a bedroom or accessing a picture folder and that social and spatial dichotomies examined in architectural and geological research fields do exist in a smartphone environment in a way it makes sense such as front and back. Lastly, we realized that while the household environment provided static feeling overall, the smartphone environment provided dynamic feeling.

Reliability-Based Design Optimization (RBDO) for Electric Vehicle Market Systems

When designing a product, both engineering uncertainty and market heterogeneity should be considered to reduce the risk of failure in the market. Reliability-based design optimization (RBDO) approach allows decision makers to achieve target confidence in product performance under engineering uncertainty. Design for market systems (DMS) approach helps decision makers to find profit-maximized product design under market heterogeneity. This paper integrates RBDO and DMS approaches for an Electric vehicle (EV) design. Consumers’ preferences on warranted battery lifetime are heterogeneous while battery life itself is affected by various uncertainties such as battery characteristics and driving patterns. We optimized and compared four scenarios depending on whether engineering systems are deterministic or probabilistic, and whether a market is homogeneous or heterogeneous. The results provide some insight on how the optimal EV design should be altered depending on engineering uncertainty and market heterogeneity.

Convergence Strategy for Parallel Solving of Analytical Target Cascading with Augmented Lagrangian Coordination

Analytical Target Cascading (ATC) is a decomposition-based optimization methodology that partitions a system into subsystems and then coordinates targets and responses among subsystems. Augmented Lagrangian relaxation with Alternating Direction method (AL-AD) has been widely used for the coordination process of both hierarchical ATC and non-hierarchical ATC, and theoretically guarantees convergence under the assumption that all subsystem problems are convex and continuous. One of the main advantages of ATC is that it can solve subsystem problems in parallel, thus allowing it to reduce computational cost by parallel computing. Previous studies have proposed AL coordination strategies for parallelization by eliminating interactions among subproblems. This is done by introducing a master problem and support variables or by approximating a quadratic penalty term to make subproblems separable. However, conventional AL-AD does not guarantee convergence in the case of parallel solving. Our study found that, in parallel solving using targets and responses of the current iteration, conventional AL-AD causes mismatch of information in updating the Lagrange multiplier (LM). Therefore, the LM may not reach the optimal point, and as a result, increasing penalty weight causes numerical difficulty in the AL penalty function approach. To solve this problem, we propose a modified AL-AD for parallel solving in non-hierarchical ATC. The proposed algorithm uses the subgradient method with adaptive step size in updating the LM, which is independent of quadratic penalty terms and keeps quadratic penalty terms at the initial value. Without approximation or introduction of an artificial master problem, the modified AL-AD for parallel solving can achieve similar accuracy and convergence with much less computational cost, compared with conventional methods.

A Real Options Approach to Hybrid Electric Vehicle Architecture Design for Flexibility

Manufacturers launch new product models at various time increments to meet changing market requirements over time. At each design period, product design and price may change. While price decisions can be made at product launching time, redesign decisions must be made in advance. Real options theory addresses such time gap decisions. This paper presents a real options approach with a binomial lattice model to determine optimal design and price decisions for hybrid electric vehicles (HEVs) that maximize expanded net present value of profit under gas price uncertainty over time. Results confirm that we can obtain changing vehicle attributes by changing gear ratios rather than the architectures themselves due to high cost of redesigning. A parametric study examines the impact of gas price volatility on option decisions and shows that larger volatility of gas price causes the change option to be selected more frequently. NOMENCLATURE X Design at time t P (t) Price of a new design at time t P ′(t) Price of the current design at time t V (t) Profit at time t PV (t) Present value of profit at time t I Initial investment NPV (0) Net present value of whole design project ni i-th node at time t ∗Address all correspondence to this author. p Probability of gas price being increasing u Proportional increase in gas price d Proportional decrease in gas price σ Volatility of gas price G Initial gas price r Risk-free interest rate C Redesign cost ρ Planetary gear ratio FR Final drive ratio