Electric Mobility Research Articles

Adaptive Multi-Agent Reinforcement Learning for Optimizing Dynamic Electric Vehicle Charging Networks in Thailand

The rapid growth of electric vehicles (EVs) necessitates efficient management of dynamic EV charging networks to optimize resource utilization and enhance service reliability. This paper explores the application of adaptive multi-agent reinforcement learning (MARL) to address the complexities of EV charging infrastructure in Thailand. By employing MARL, multiple autonomous agents learn to optimize charging strategies based on real-time data by adapting to fluctuating demand and varying electricity prices. Building upon previous research that applied MARL to static network configurations, this study extends the application to dynamic and real-world scenarios, integrating real-time data to refine agent learning processes and also evaluating the effectiveness of adaptive MARL in maximizing rewards and improving operational efficiency compared to traditional methods. Experimental results indicate that MARL-based strategies increased efficiency by 20% and reduced energy costs by 15% relative to conventional algorithms. Key findings demonstrate the potential of extending MARL in transforming EV charging network management, highlighting its benefits for stakeholders, including EV owners, operators, and utility providers. This research contributes insights into advancing electric mobility and energy management in Thailand through innovative AI-driven approaches. The implications of this study include significant improvements in the reliability and cost-effectiveness of EV charging networks, fostering greater adoption of electric vehicles and supporting sustainable energy initiatives. Future research directions include enhancing MARL adaptability and scalability as well as integrating predictive analytics for proactive network optimization and sustainability. These advancements promise to further refine the efficacy of EV charging networks, ensuring that they meet the growing demands of Thailand’s evolving electric mobility landscape.

Modelling the complementarity and flexibility between different shared modes available in smart electric mobility hubs (eHUBS)

eHUBS are physical locations that integrate two or more electric shared mobility modes. As they provide transport users easier access to a wide range of transport modes, multimodal behaviour is expected to be more common. However, this issue has not been addressed in previous stated preference studies on mode choices involving innovative transport modes. In this study, multimodal behaviour is explicitly addressed both in measurement and in modelling by adopting the multiple discrete–continuous (MDC) modelling framework in contrast to discrete choice models. Instead of asking transport users to indicate the most preferred alternative, they were allowed to choose more than one alternative by allocating trips between several modes. This study aims to answer two questions: 1) whether there is complementarity between the multiple shared modes offered in eHUBS and 2) how would transport users adapt when one of the shared modes that they plan to use becomes unavailable. Using stated mode choice data of non-commuting trips from transport users whose current mode is driving a private car in Manchester, UK, several models under the MDC framework were estimated including Multiple Discrete-Continuous Extreme Value (MDCEV) model, mixed MDCEV model, and the extended Multiple Discrete Continuous (eMDC) model. The results show that there is complementarity between shared electric vehicle (EV) and electric bike (e-bike) offered in the eHUBS. In addition, the research show that the flexibility between those two shared modes is stronger than assumed in the MDCEV model, and common preference heterogeneity cannot fully account for this phenomenon.

Towards a circular business ecosystem of used electric vehicle batteries – A modelling approach

The increase in electric mobility will result in a growing number of used batteries that require an efficient system for handling and recycling valuable materials. The purpose of the research is to create a model of the business ecosystem for post-consumer electric vehicle batteries to identify circular economy business opportunities and limitations. Applying the ecosystem pie modelling methodology, the critical actors involved in electric vehicle battery repurpose and recycling are mapped, including the interdependencies and risks. The modelling is based on interviews with several industrial ecosystem actors and existing research literature. Opportunities and challenges in the circular business ecosystem are identified, relevant to industry strategists and decision-makers. The research findings reveal that downstream circular business ecosystems are more unpredictable and unplanned than upstream linear business ecosystems. The study also highlights the trend towards vertical integration among actors in the battery industry to secure the supply of materials.

Towards full electrification of local public transport: A tool to guide strategies for implementing the electric charging network

This paper describes a methodology and a Decision Support Tool (DST) for the assessment of the impacts of future scenarios of public electric mobility on the electric Distribution Network (DN) of a city, aimed to support the implementation strategies of the electric charging network for the Local Public Transport (LPT).The objective of the proposed tool is supporting the decision makers in estimating the effect of the future development of electromobility on the urban electric grid considering the evolution of both electric buses and their charging infrastructure.Some scenarios for the development of electric charging infrastructure for LPT were identified together with the local public transport operator and the energy provider. The results, which are of interest to both the local Public Transport Operator (PTO) and the local Distribution System Operator (DSO), have been quantified for the city of Turin (Italy), but the methodology can be adopted in any urban context: DSOs and PTOs of each city can use the proposed tool as a support to define their public transport electrification strategies.Some results from the case study examined in this paper (Turin, Italy) show that the energy demand related to the electrification of LPT on a typical weekday is about 45 MWh in 2030 (corresponding to 40 % e-bus), and about 90 MWh when the entire bus fleet is electric. It is also shown how more distributed recharging during the day (with intermediate recharging at the terminus) can dampen the energy/power peaks required at the depot compared to overnight recharging alone: a reduction of up to 27 % of energy demand at the depot is observed due to opportunity charging.

India's Shift to Electric Mobility

The Automotive sector is a pivotal contributor to India’s economic growth and contributes 49% to India’s manufacturing GDP. In FY24, the country produced approximately 49 lakh passenger vehicles, 9.9 lakh three-wheelers, 214.7 lakh two-wheelers, and 10.7 lakh commercial vehicles. The world’s primary modes of transportation are facing two major problems: rising oil costs and increasing carbon emissions. As a result, electric vehicles (EVs) are gaining popularity as they are independent of oil and do not produce greenhouse gases. However, despite their benefits, several operational issues still need to be addressed for EV adoption to become widespread. This research delves into the evolution of EVs over time and highlights their benefits, including reducing carbon emissions and air pollution. India's transition from traditional internal combustion engines (ICE) to electric vehicles (EVs) is driven by a combination of environmental, economic, and policy factors. This shift is aimed at reducing the country's dependency on fossil fuels, lowering carbon emissions, and promoting cleaner air, particularly in urban areas plagued by pollution. Government initiatives such as the Faster Adoption and Manufacturing of Hybrid and Electric Vehicles (FAME) scheme.

Energy transition in Portugal: The harnessing of solar photovoltaics in electric mobility and its impact on the carbon footprint

The ambition to achieve carbon neutrality by 2050, reinforced by international agreements, requires both the reduction of gas emissions in the transport sector and the acceleration of the realization of the energy transition. There is therefore growth potential for electric mobility and photovoltaic technology. In this context, this study explores the integration of electric vehicles into the Portuguese car fleet using photovoltaic solar energy for battery charging, with the aim of reducing greenhouse gas (GHG) emissions and reducing dependence on fossil fuels for mobility. A multi-phase approach was adopted: i) a sample of electric vehicles representative of the Portuguese car fleet and their energy needs was sized; ii) the equipment to be incorporated into the Self-Consumption Production Units was selected and sized, using PVsyst software version 7.3.4, and based on the energy needs resulting from three scenarios of weekly use of the electric vehicle [50 km (scenario 1), 300 km (scenario 2) and 750 km (scenario 3)]; iii) the reductions in GHG emissions were quantified by analysing: emissions from the Public Service Electricity Grid (RESP) and the Photovoltaic Integration System for Self-Consumption and Grid (SIFAR), and also emissions associated with the fossil fuels under analysis (petrol and diesel). In scenario 1, the difference was 57.5%. In scenario 2, it was −24.3%, and in scenario 3, it was −55.9%. These results demonstrate that SIFAR is an attractive and more sustainable alternative to RESP in the most energy-demanding scenarios, in this case, scenarios 2 and 3. By contributing to a considerable reduction in GHG emissions into the atmosphere, SIFAR stands out for its role in building sustainability. Presenting a new methodological perspective and vision on the integration of renewable energies in the transport sector in Portugal, this study closes a knowledge gap and provides relevant information for planning and public policy.

Experimental modal identification of a pedestrian bridge through drive-by monitoring integrated with shared-mobility vehicles

In the context of improving resilience in transport infrastructure, an emerging approach of indirect structural health monitoring is gaining attention, known as drive-by monitoring, instrumenting a vehicle with sensors to evaluate the bridges it crosses. However, their effectiveness has predominantly been investigated in ideal scenarios, with actual real-world applications being quite scarce. The research presented in this paper explores the feasibility of combining two routes: (1) fleet emissions reduction and (2) transport resilience enhancement, through drive-by monitoring integrated with shared mobility, including electric mobility scooter and bicycle. The information from drive-by data collected from shared mobility can give valuable information on critical transport infrastructure (e.g., bridges) and such a drive-by database has the potential for network level infrastructure condition assessment. In this paper, two different drive-by roadmaps are investigated subject to the flexibility of the bridges, namely partially or fully drive-by monitoring. To validate the proposed roadmaps, a full-scale pedestrian bridge was chosen for drive-by testing, where smartphone sensors and specialised accelerometers are mounted on shared mobility for data acquisition. Experimental results demonstrate that (i) smartphone sensing can provide data with similar accuracy compared to specialised accelerometers, (ii) bridge frequencies can be easily obtained from temporarily parked shared mobility, with a maximum relative error of 1.05%, (iii) both the bridge frequencies and operational deflection shapes are successfully extracted from the moving shared mobility by using variational mode decomposition and filtering techniques, and shared mobility’s GPS data along with moving speeds are collected for potential vehicle positioning and drive-by database updating.

Scalable Innovative Factors for Shaping Consumer Intentions on Electric Two-Wheelers Adoptions

Electric two-wheelers (ETWs) have emerged as a dominant choice over traditional counterparts in global consumer markets, prompting a shift in consumer behaviour. While existing research has delved into the adoption of ETWs, there remains a notable gap in understanding the intricate factors driving consumer adoption, particularly their inclination toward innovation. This study investigates the landscape of ETWs in India, focusing on facilitating conditions, pricing dynamics, personal innovativeness, and behavioral intentions. Utilizing the Unified Theory of Acceptance and Use of Technology (UTAUT) framework, 220 Indian ETW users were surveyed to elucidate the interplay between facilitating conditions, price, and behavioral intentions, mediated by personal innovativeness. The findings underscore the significant impact of facilitating conditions and price on behavioral intentions, with personal innovativeness serving as a pivotal mediator in this relationship. Moreover, this study underscores the importance for ETW businesses to prioritize user-friendly designs, ensuring a seamless and enjoyable experience for consumers. Furthermore, targeting highly innovative consumers emerges as a strategic imperative for businesses in devising effective marketing strategies. By shedding light on facilitating conditions, price dynamics, personal innovation, and behavioral intentions, this study contributes valuable insights to the existing literature. In terms of environmental sustainability, the scalability of electric twowheelers contributes to reducing greenhouse gas emissions and mitigating air pollution in urban areas. As more individuals switch from gasoline-powered vehicles to electric two-wheelers, the collective impact on reducing carbon emissions and improving air quality becomes increasingly significant, especially in densely populated regions where transportation-related pollution is a major concern. Additionally, it offers a nuanced understanding of the mediating role of personal innovation in the context of ETWs, thereby informing future research and strategic initiatives in the field of electric mobility.

Environmental Knowledge, Awareness, Attitude Toward Purchase Intention, Mediated by Infrastructure Readiness & Price Affordability of Electric Vehicle (EV): Case in Indonesia

The study investigates the impact of electric vehicle (EV) technology on Indonesia's automotive industry and economy, emphasizing EVs' role in emission reduction. Factors affecting EV uptake, including purchasing behavior and environmental awareness, are analyzed, contributing to the theory of planned behavior. Data from 136 respondents were collected through surveys, revealing positive correlations between environmental awareness, knowledge, attitude, and purchase intent. Price affordability emerges as an intervening variable. The study offers insights for the gradual integration of EVs into Indonesia's automotive sector, highlighting initiatives by both manufacturers and the government, such as introducing EV options and implementing regulations related to energy, charging infrastructure, and taxation. This research underscores the importance of addressing consumer perceptions and market dynamics to facilitate the transition toward electric mobility in Indonesia.

OPTIMIZATION OF AN INTELLIGENT CONTROLLED BRIDGELESS POSITIVE LUO CONVERTER FOR LOW-CAPACITY ELECTRIC VEHICLES

This paper presents a novel approach to power conversion in electric vehicle (EV) applications. The proposed converter, a Bridgeless Single Stage Positive Luo Converter (BSPLC), is optimized to enhance efficiency and reduce losses in low-capacity EVs. Traditional converters experience higher losses due to their passive components and bridge circuits. By eliminating the bridge components, the converter achieves higher efficiency. An intelligent fuzzy logic controller is employed to provide adaptive control and stabilize output under varying input conditions, improving performance and response time. The converter design is further optimized through parameter tuning and simulation to achieve minimal ripple and maximum power efficiency at 92%. The proposed solution is ideal for low-capacity EVs, as it ensures enhanced power conversion, reduced thermal stress, and improved battery life. The study demonstrates the converter’s capability to meet the growing demands for energy-efficient solutions in modern electric mobility.

Flexoelectronics of a centrosymmetric semiconductor cylindrical nanoshell

Cylindrical shell-type semiconductors are essential for sensing and energy harvesting when integrated into surfaces of certain equipment, such as spacecraft, marine devices, and portable electronics, where mechanical forces play a significant impact on charge transport. Traditionally, such functionalities are only manifested in piezoelectric or pyroelectric crystals that possess non-centrosymmetry. Here, we theoretically investigate electronic behaviors driven by strain gradient-induced flexoelectric polarization in a centrosymmetric semiconductor cylindrical nanoshell, expanding the flexoelectronics in shell structures. The governing equations and accompanying boundary conditions are formulated simultaneously using the principle of virtual work and the fundamental lemma of the calculus of variation. Electromechanical interactions through static bending and forced vibration analyses of the newly developed model are systematically investigated. Under localized force excitation, the distribution of mobile charges is manipulated by tuning loading magnitudes and areas. The effects of doping levels on electric potentials and mobile charges are explored to show the interaction mechanism between flexoelectric and semiconducting properties. Moreover, the natural frequencies and modes of all mechanical displacements, electric potentials, and carrier concentration perturbations within the shell are identified. This paper provides a new approach for designing shell-shaped sensors and energy harvesters specifically for centrosymmetric semiconductors.

Analysis of semiconductor properties of fabricated graphene materials

Introducing dopant elements into graphene is a crucial process for creating bandgaps, which will have significant importance in developing nanoelectronic devices in the future. In this study, we provide an analysis of the electrical and carrier mobility properties of graphene doped with BN in ratios of 1 %, 3 %, and 5 %, graphene 95 %, ZnO-3 %, and BN2 %, graphene-95 %, Al2O3-3 % and BN-2 %, graphene-95 %, TiO2-3 % and BN-2 % by using a sintering process. Upon analyzing the band structure, it was determined that the mentioned materials demonstrate a bandgap in graphene. The resistivity values for fabricated graphene materials doped with different nanoparticles are estimated using the Source-meter Unit (SMU) at room temperature (25°C), 100°C and 200°C. The conductivity of graphene is 8.93E+07 Ω−1cm−1 and reduced gradually with the doping percentages. The resistivity of graphene is measured at 1.12 E-08 Ω.cmand increases with the doping percentages, and carrier mobility is measured to be 9239 cm2V−1s−1 and gradually reduced with the doping percentages. The temperature-dependent conductivity is determined using electrical conductivity under the constant relaxation time approximation.

Enabling role of policies to make public charging infrastructure development viable in an Indian city: A modelling-based analysis

The present paper is concerned with shedding light on the financial viability of setting up public charging infrastructure in a range of implementation situations in an Indian city and the possible role of policies and regulations to make charging business attractive. The nascency of the electric mobility sector and its fast-evolving technological landscape along with possibility of different charging use-cases make it difficult to templatize the financial evaluation of charging business. With the help of a publicly available peer-reviewed financial tool which has been specifically developed to analyze the possible financial outcome of an investment in public charging infrastructure for electric vehicles (EVs) in Indian context, the study examines the business attractiveness of setting up a public charging station in four unique use-cases such as charging at public parking, destination charging, on-the-go charging, and shared workplace charging. The study employs Project Internal Rate of Return as the primary financial yardstick that is being benchmarked with a hurdle rate or target rate of return to make the evaluation as objective as possible. The financial modelling aptly captures the dynamics of India’s EV charging market by considering the possible variations in charging infrastructure configuration, electricity tariffs and regulations, provision for land rental, charging fees and other such factors. It further demystifies the potential impact of key variables on a project’s business case. This research would help design policies, regulations, support mechanisms and terms of reference for public charging infrastructure projects in the country. Policymakers, implementing authorities, regulators, potential investors, and financial institutions are expected to benefit from the analyses.

Dataset on Electric Road Mobility: Historical and Evolution Scenarios until 2050

An increasing adoption of electric vehicles (EVs) is expected in the coming decades mainly due to the need to achieve carbon neutrality until 2050. However, predicting electric mobility’s future is challenging due to three main factors: technological advancements, regulatory policies, and consumer behaviour. The projections presented in this study are based on several scenarios driven mainly from reports published by public entities and consultants. It considers the evolution of electric road mobility by defined targets in the electrification of the transport sector. Therefore, the gathered data addresses different horizon times regarding EV penetration in the World, Europe, Portugal, Denmark, Greece, and Slovenia. Thus, an extensive literature review and estimating approach for EV forecast was conducted concerning EV markets, charging infrastructure, and electricity demand. Also, the dataset aims to provide a demand projection by 2050 and serving as a critical input to further work on EV mass deployment in the context of the project Electric Vehicles Management for carbon neutrality in Europe (EV4EU) and other works related to this field.

A Photovoltaic and Wind-Powered Electric Vehicle with a Charge Equalizer

This research aims at proposing an alternative to improve the efficiency of electric vehicles (EVs) and reduce greenhouse gas (GHG) emissions in the context of electric mobility. A photovoltaic and wind hybrid energy system was installed in a Chok S2 electric vehicle. In addition, a charge equalization system was included to balance and maximize the performance of each of the EV’s five batteries connected in series. The results show a 20% improvement in vehicle efficiency after conducting tests on a 17 km Andean route. The photovoltaic system generated 535 W, while the wind system generated 135 W/s at a speed of 45 km/h. These findings highlight the potential of hybrid renewable energy systems to improve the efficiency and range of electric vehicles.

Waste polyethylene terephthalate-derived organic-inorganic hybrid materials as sustainable dual electrodes for Li-ion batteries

The hybrid Fe-Li2TP structure is constructed from waste polyethylene terephthalate (w-PET) derived dilithium terephthalate (Li2TP) and conventional Fe2O3 by hydrothermal reaction. It is being studied for both anode and cathode for LIBs. As an anode, it exhibits a reversible capacity of 505 mAh/g after 100th cycle at 1 C-rate with ∼100 % coulombic efficiency (CE). In addition, as a cathode, it shows highly reversible charge/discharge capacities of 107.50/107.52 mAh/g after the 100th cycle at 0.1 C-rate with 100 % CE. Further, in the cathodic studies via galvanostatic intermittent titration technique (GITT), the average lithium diffusion (DLi+) coefficients are calculated to be 2.96 × 10-10, 3.89 × 10−10 cm2 s−1 and the electrical (µ) mobilities to be 5.86 × 1011 m2 V−1 s−1, 1.12 × 1011 m2 V−1 s−1 for charge and discharge pulses, respectively. The combined nano-rod and nano-spherical morphologies reduce the diffusion length, and adding 10 % SWCNTs during electrode fabrication enhances the electronic conductivity. This organic–inorganic hybrid strategy of Fe-Li2TP strongly mitigates the electrode dissolution, reducing the structural strain and preventing electrolyte decomposition at higher voltage. Computational studies show an optimized Fe-Li2TP structure with a 2.7-fold lower band gap value (1.9040 eV) than the pristine Li2TP.

Commercial EV fleet smart charging for cost reduction and renewables integration: A case study in Germany

The transition to electric mobility reduces transportation carbon emissions but presents challenges in integrating growing electricity demand with renewable electricity generation and power systems. Smart charging emerges as a key technology to minimize operational costs and support higher utilization of green electricity for electric vehicles (EVs). Market analysis indicates a trend towards dynamic electricity tariffs, incentivizing EV charging at times favourable to the electricity grid, yet existing literature fails to address smart charging technology in sync with times of lower electricity prices and higher renewables integration. This work examines different smart charging strategies for a commercial EV fleet in Germany, considering a Real-Time Pricing (RTP) tariff indexed to day-ahead market prices and renewable electricity integrations. HOMER Grid is used to model these smart charging strategies and generate new EV load profiles. Direct and indirect CO2 emissions and renewable electricity usage ratios are calculated based on detailed electricity grid and self consumption data. The resulting Levelized Cost of Energy (LCOE) is minimized, by adjusting solar PV and battery capacities. The adoption of an RTP tariff decreases the LCOE from €0.530 to €0.314 per kWh. A smart charging strategy designed to reduce peak demand and schedule charging at lower price times further reduces the LCOE to €0.283 per kWh. The lowest LCOE of €0.281 per kWh is achieved with 34.4 kWp of solar PV capacity and no batteries. The carbon impact is minimized with larger solar PV and battery capacities. The performed work indicates a favourable framework for EV charging integrators to maximize cost savings and renewable energy integration for an EV fleet charging use case.

Sustainable Business Models for Innovative Urban Mobility Services

Any sharing mobility service aims to make urban mobility sustainable to help reduce environmental impacts and improve the quality of life for all in cities. Many transport services are not currently self-sustainable. The Life for Silver Coast (LifeSC) opened its mobility services on 22 May 2021 and offered electric mobility services during the summer for a few cities in Tuscany. E-bikes and e-scooters can be financially neutral, and even profitable, thanks to the low costs of the vehicles, but they only see a high utilization rate in winter. Shared electric cars, meanwhile, are not profitable. A new shared service that is viable must be profitable to become widely adopted and significantly contribute to sustainability. A few key characteristics have been identified, and one has been tested with a new business model that combines ride-sharing and car-sharing. The innovative Ride Sharing Algorithm (RSA) has been tested based on data from a potential city, Monterondo, where many commuters travel daily to Rome by train. The Italian census and local survey data allowed for the simulation of the scheduling of vehicle rides and an evaluation of the economic results, which could be positive if enough interest for such a system exists among the people, as at least 400 commuters from Monterotondo go to the train station daily in the morning and return in the afternoon. Such a transport demand would justify a new commercial sharing service by using the model tested with the RSA algorithm.

A particle swarm optimizer-based optimization approach for locating electric vehicles charging stations in smart cities

Conventional fossil fuel-powered vehicles are gradually being replaced by electric and hydrogen vehicles in the transportation sector. Even with all the recognized benefits and recent advancements in energy efficiency, decrease of noise, and environmental impact reduction, the market of electric and hydrogen mobility is still not up to par. Allocating charging stations in metropolitan areas for electric vehicles is considered as one of the most significant obstacles preventing electric and hydrogen vehicles from becoming more widely used. In this paper, an efficient approach aimed at finding optimal locations for electric vehicles (EV) charging stations in urban areas is proposed. Particle Swarm Optimization algorithm technique is utilized with the proposed approach. Various parameters were taken into consideration in this work, such as the horizontal distance that EVs travel to reach charging stations (CSs), and positive slope that EVs face to reach charging stations. The optimization problem is formulated as a Mixed-integer problem. The objective function works on minimizing the energy consumption of EVs to reach CSs in the investigated area. Difference constraints are incorporated with the proposed approach in order to increase the accuracy and efficiency of the proposed approach. The proposed approach is applied on real world datasets and is experimentally validated using through comparison with Genetic Algorithm and the greedy approach. The results demonstrate that the proposed approach saves energy about 22% and 43% compared to the genetic algorithm and greedy technique, respectively.

Barriers to Electrification: Analyzing Critical Delays and Pathways Forward

This paper extensively explores the intricate nuances surrounding the delayed transition to new business models for electric vehicles. While there is commendable clarity regarding stakeholders, model possibilities, emission-reduction strategies, state aid initiatives, and citywide prohibitions, the central challenge lies in the gradual pace of this transition. Notably, the persistent high costs of electric vehicles, primarily attributed to exorbitant battery prices and the raw materials involved, represent a formidable hurdle to widespread adoption. In this article, a comprehensive examination of the multifaceted aspects contributing to the delays in the shift towards electrified transport is proposed. By meticulously scrutinizing the intricacies of this delay, the aim is to provide valuable insights that can contribute to accelerating the adoption of electric vehicles. The exploration of these challenges is essential for fostering a nuanced understanding of the impediments hindering the transition and, subsequently, for devising effective strategies to overcome them. The analysis presented herein not only identifies the hurdles but also seeks to offer potential solutions and strategies that can drive the transformative change needed in the realm of electric transportation. Understanding and mitigating the barriers impeding the transition is crucial for fostering a rapid and successful shift towards electric mobility in Spain, ensuring a sustainable and efficient transportation landscape for the future.