PhD Student at École de technologie supérieure studying Carbon Nanotube MEMS.
Can Tesla beat the likes of Ford and GM to take over the automotive world?
What exactly is the future of cars? The auto industry’s fate rides on the answers to three unresolved questions: driven or self-driving? Electric or gas? Private or shared? Tesla's value A couple of weeks ago Tesla surged past automotive giants like Ford and GM to become the most valuable car company in the USA. For a firm that has existed for less than 2 decades, that is incredible. That sounds impossible It does indeed and the numbers also stand against Tesla. Tesla sold 80,000 cars last year. GM sold 10 million, meaning it exceeded Tesla’s annual vehicle sales every three days, on average. Despite the fanfare, Musk’s company lost $780 million in 2016. Ford made $11 billion. The future of Cars Right now, there is a huge focus on "self-driving cars" and this begs the question Will people drive cars, or will the cars drive themselves? The self-driving revolution is like a massive West Coast earthquake—experts claim it’s practically inevitable, but nobody can say for sure when or what it will look like. If this self-driving future never fully materializes, legacy car companies will probably benefit from the lack of disruption. But is it so obvious that they would also lose, even in the self-driving scenario? Is the future of cars electric, or something else? One of the most attractive points about Tesla is that it does not make fuel driven cars, their products are all purely electric and it is also worth mentioning that they are loaded with the best technology available. Several automakers, like General Motors and Honda, are dabbling in other clean energy, like fuel-cell systems. But hydrogen fueling stations cost about $2 million to build and there are only 34 in the United States today, with more than half in one state—California. Given the technology’s questionable viability, it is more likely that the technology will navigate more towards battery driven cars. Electric vehicles also have the benefit of tax credit benefits in almost all the countries which is a very attractive proposition for potential buyers. It does look very promising for Tesla Indeed, with manufacturers still struggling to catch up to Tesla, it is just a matter of time that Tesla becomes a behemoth in the auto industry and perhaps even save the environment. It is a waiting game.
Abstract: Electric vehicles (EV) are treated as a breakthrough technology in the automotive market. The novelty of this technology also implicates that the incidence of these vehicles worldwide is still low. An important issue regarding EVs is the existence of proper charging infrastructure as waiting at charging stations due to an inadequate number of chargers can discourage EV owners. However, as the number of EVs and charging stations are low at present, real world experience is not available, so computer simulations are required for the planning of such charging stations.
Pub.: 17 Feb '17, Pinned: 30 Apr '17
Abstract: This article analyses the electric-and-gasoline vehicle market under two different structures: monopoly and duopoly. Taking social welfare into account, the government offers a subsidy incentive scheme or a price discount incentive scheme to buyers of electric vehicles (EVs) to promote the adoption of EVs. We formulate a utility model composed of a population of consumers who make utility maximizing choices and manufacturers who set an optimal pricing that responds to the interventions of the government. Using this model, a framework for policy makers to find optimal subsidies or optimal price discount rates is developed. Unlike the monotonic relation in the monopoly setting, in the duopoly setting the relationship between consumers’ low-carbon awareness and EVs’ demand depends on the government’s policy. Although the demand for EVs, the consumer surplus, the environmental impact, and the social welfare are identical under two incentive schemes, the government prefers to implement a subsidy incentive scheme due to the lower expenditure involved. Furthermore, under a subsidy incentive scheme, EVs’ market in the monopoly setting has a smaller environmental impact than that in the duopoly setting. From the numerical tests, we show that results of social welfare comparison under two market structures depends on unit environmental impact of EV.
Pub.: 21 Apr '17, Pinned: 30 Apr '17
Abstract: The transition from fuel cars to electric cars is a large-scale process involving many interactions between consumers and other stakeholders over decades. To explore how policies may interact with consumer behavior over such a long time period, we developed an agent-based social simulation model. In this model, detailed data of 1795 respondents have been used to parameterise an agent architecture that addresses different consumer needs and decision strategies. Numerical experiments indicate that effective policy requires a long-lasting implementation of a combination of monetary, structural and informational measures. The strongest effect on emission reduction requires an exclusive support for full battery electric cars and no support for hybrid cars.
Pub.: 16 Jan '17, Pinned: 30 Apr '17
Abstract: Increasing long-term gasoline price and concerns on the impact of emissions have inspired alternative technologies like electric vehicles (EVs). As a part of the initiative to improve local air quality, cities encourage the adoption of EVs in mass transit system, in particular taxicabs. Motivated by the above, we study a fleet environment, like taxicabs, and build a model that captures the factors influencing EV adoption. We consider a vertically-integrated entity that is a combination of a taxicab company and an infrastructure service provider. We model the entity’s decision-making problem that includes (i) fleet renewal using either internal combustion engine vehicles (ICEs) or EVs; and (ii) infrastructure planning corresponding to investing in fast chargers, and swap stations with stocked EV batteries. We characterize EV adoption in terms of problem parameters such as the mean and coefficient of variation of miles driven. We find that the adoption decision can switch between adopt and do not adopt and vice versa as the mean miles increases. EVs may be adopted at higher variability in miles driven even when they are not adopted at lower variability. To address the operational characteristics of taxicabs to a greater extent, we relax key model assumptions and find that the above conclusions based on the mean and coefficient of variation of miles driven remain valid. This research has practical implications on the attractiveness (or lack thereof) of EV taxicabs / swap stations and on the impact of various government or R&D improvement actions on EV adoption.
Pub.: 19 Mar '17, Pinned: 30 Apr '17
Abstract: Plug-in electric vehicles increasingly augment their share in the global market as they appear to be an economic and emission-free alternative to modern means of transportation. As their presence strengthens, ways that will ensure economic charge along with uninterrupted grid operation are necessary to be found. This paper aims to approach the economic optimization problem that includes several Electric Vehicles (EVs) within a Low Voltage (LV) network comprising various Distributed Energy Resources (DER) as fuel cell, Renewable Energy Sources (RES), (photovoltaics, wind turbine) etc. via a scenario based simulation. The purpose is to investigate the main variables of the grid, such as its operating cost, charging patterns, power injection from the upstream network, resulting from the coordinated control of DER in Smart Microgrid operation in conjunction to the flexible load the controlled EV charging introduces. The base case study is that of absence of EVs, and therefore the demand is met only by the upstream network and the DER units. Subsequently, EVs are introduced as controllable loads and finally as dispatchable storage units incorporating a Vehicle to Grid (V2G) capability to the Smart Microgrid. Furthermore, the problem is not tackled deterministically and although forecasts for all network parameters are assumed to be known, forecasting errors and stochastic driver patterns cannot be ignored. Thus, for each imposed policy, a scenario based approach is implemented to determine operating cost in various cases along to DER utilization and the effect EVs bear on these results.
Pub.: 03 Mar '17, Pinned: 30 Apr '17
Abstract: Electric and hybrid vehicles are a big step towards a greener mobility, but they also open up completely new questions regarding the shortest path problem and the planning of trips. Since recharging an electric car will take much longer than refilling conventional fossil fuels, we have to balance between speed and range and we have to choose stops for charging wisely. For hybrid vehicles, a symbiosis between navigation system and power train control to choose a path with optimal phases for depleting and recharging the battery may yield much more energy-efficient paths. In this paper, we develop an appropriate model for finding shortest routes for these kinds of vehicles, which is mainly a constrained shortest path problem with convertible resources and charging stations. We study properties of solutions by classifying several types of cycles that may occur in the optimal route. We state sufficient conditions to exclude some of these cycle classes and we derive appropriate approximation schemes with provable quality and strict feasibility. We also study the related network flow problem for operating fleets of electric vehicles, e.g., shared vehicles or buses in urban areas.
Pub.: 25 Mar '17, Pinned: 30 Apr '17
Abstract: The Korean government is planning to increase the number of its hydrogen stations from 20 in 2016 to 100 by 2020, to enhance the use of hydrogen fuel cell electric vehicles and to reduce greenhouse gas (GHG) emissions. This article looks at the public willingness to pay (WTP) for implementing the expansion policy. To this end, a contingent valuation survey of 1000 Korean households was implemented. To mitigate the response effect in eliciting the WTP and to increase the statistical efficiency of the analysis of the WTP data, we employed a one-and-one-half-bounded dichotomous choice question format. Furthermore, we used a spike model to model the WTP responses with zero observations. The mean yearly WTP for the policy implementation is computed to be KRW 2258 (USD 2.04) per household, which is statistically significant at the 1% level. The national annual value amounts to KRW 42.8 billion (USD 38.6 million). This value can be taken as an indication of the external benefit of the reduction in GHG emissions by means of the expansion.
Pub.: 11 Apr '17, Pinned: 30 Apr '17
Abstract: Lithium sulfur batteries, one of the most promising energy storage methodologies for emerging electric vehicles, suffer from poor long-term cycling stability due to the shuttle effect caused by the dissolution of high order polysulfides. To enhance the cycling stability of sulfur cathode for high-energy lithium sulfur batteries, it is very critical to mitigating the dissolution of polysulfides. In this work, a caterpillar-like and reconfigurable graphene was designed to serve as the sulfur host. The caterpillar-like graphene highly expanded in solution and tightly restacked in dry condition due to the van der Waals force. Elemental sulfur was trapped and confined inside the restacked graphene layers. High mass loading of 63.8% sulfur in graphene was achieved after the caterpillar-like graphene was dried at 155 °C. The graphene-sulfur electrode has a good rate performance of 708 mAh g-1 at 167.5 mA g-1, 582 mAh g-1 at 335 mA g-1, 470 mAh g-1 at 837.5 mA g-1, 400 mAh g-1 at 1675 mA g-1 and a stable cycling performance with small capacity decay of 0.16% per cycle over 200 cycles at 1675 mA g-1. Moreover, the underlying mechanism of the restacking effect of caterpillar-like graphene on immobilizing the soluble lithium polysulfides was studied by density functional theory (DFT), which clearly explained how the graphene immobilized the soluble lithium polysulfides by the restacking effect.
Pub.: 12 Apr '17, Pinned: 30 Apr '17
Abstract: Envisioned below is an energy system named Thermal Hydrogen developed to enable economy-wide decarbonization. Thermal Hydrogen is an energy system where electric and/or heat energy is used to split water (or CO2) for the utilization of both byproducts: hydrogen as energy storage and pure oxygen as carbon abatement. Important advantages of chemical energy carriers are long term energy storage and extended range for electric vehicles. These minimize the need for the most capital intensive assets of a fully decarbonized energy economy: low carbon power plants and batteries. The pure oxygen pre-empts the gas separation process of “Carbon Capture and Sequestration” (CCS) and enables hydrocarbons to use simpler, more efficient thermodynamic cycles. Thus, the “externality” of water splitting, pure oxygen, is increasingly competitive hydrocarbons which happen to be emissions free. Methods for engineering economy-wide decarbonization are described below as well as the energy supply, carrier, and distribution options offered by the system.
Pub.: 19 Apr '17, Pinned: 30 Apr '17
Abstract: This article investigates the effects of different characteristics of supplier-customer relationships in the Japanese automotive industry, and how these influence predictions about future technologies of a disruptive nature, such as Electric Vehicles (EVs). We conducted a survey of a broad set of suppliers in the Japanese automotive industry and another survey of suppliers registered with Toyota's two supplier associations. The data were used to analyse the influence of particular relationships and practices on information gathering about new technologies, preparations for R&D and production of new components, and predictions about new technologies. The study shows that suppliers’ R&D intensity and the usage degree of the drawing-supplied parts system lead to predictions favouring the uptake of new technologies. Moreover, communication between automakers and suppliers and arm's-length relationships simultaneously lead to favourable views on the future of new technologies, especially with regard to EVs. Moreover, we find that Japanese-style cooperative relationships, arm's-length relationships, communication between automakers and suppliers, and communication among suppliers all lead to less favourable views on new technology uptake (in this case, EVs). We discuss the implications of these findings for research and practice, specifically for EVs.
Pub.: 20 Apr '17, Pinned: 30 Apr '17
Abstract: A key challenge hindering the mass adoption of Lithium-ion and other next-gen chemistries in advanced battery applications such as hybrid/electric vehicles (xEVs) has been management of their functional performance for more effective battery utilization and control over their life. Contemporary battery management systems (BMS) reliant on monitoring external parameters such as voltage and current to ensure safe battery operation with the required performance usually result in overdesign and inefficient use of capacity. More informative embedded sensors are desirable for internal cell state monitoring, which could provide accurate state-of-charge (SOC) and state-of-health (SOH) estimates and early failure indicators. Here we present a promising new embedded sensing option developed by our team for cell monitoring, fiber-optic sensors. High-performance large-format pouch cells with embedded fiber-optic sensors were fabricated. The first of this two-part paper focuses on the embedding method details and performance of these cells. The seal integrity, capacity retention, cycle life, compatibility with existing module designs, and mass-volume cost estimates indicate their suitability for xEV and other advanced battery applications. The second part of the paper focuses on the internal strain and temperature signals obtained from these sensors under various conditions and their utility for high-accuracy cell state estimation algorithms.
Pub.: 05 Dec '16, Pinned: 30 Apr '17
Abstract: We propose a three-phase matheuristic, combining an exact method with a Variable Neighborhood Search local Branching (VNSB) to route a fleet of Electric Vehicles (EVs). EVs are allowed stopping at the recharging stations along their routes to (also partially) recharge their batteries. We hierarchically minimize the number of EVs used and the total time spent by the EVs, i.e., travel times, charging times and waiting times (due to the customer time windows). The first two phases are based on Mixed Integer Linear Programs to generate feasible solutions, used in a VNSB algorithm. Numerical results on benchmark instances show that the proposed approach finds good quality solutions in reasonable amount of time.
Pub.: 14 Apr '17, Pinned: 30 Apr '17