Gasoline Cars Research Articles

Assessment major NOx sources to nitrate of TSP around the Danjiangkou reservoir using isotopes and a Bayesian isotope mixing model

Nitrate (NO3−) is a key component of atmospheric particulate matter. However, studies quantifying NO3− formation and sources in water source areas remain scarce. This study employs NO3− concentration, dual isotopic analyses (δ15N, δ18O), and SIAR and PSCF models to elucidate NO3− formation mechanisms and apportion sources in the Danjiangkou Reservoir area. The result showed that the concentration of NO3− (0.52 μg m−3-2.39 μg m−3), δ15N–NO3- (−2.3‰-4.2‰) and δ18O–NO3- (64.2‰–96.6‰) values varied seasonally in total suspended particulate matter (TSP). The contribution of the NO2 + ·OH pathway was the highest in summer (84%), while the main contributions came from the N2O5 + H2O and NO3 + VOCs pathways in winter (75%). The SIAR model revealed that the contributions of coal combustion and traffic emissions were 34% and 23%, respectively, indicating that fossil fuel release contributed most. Moreover, the contribution of biomass combustion sources was 31%, and soil emission sources had the least (12%). Considering liquefied petroleum gas, gasoline, and diesel vehicles as traffic emission sources, their contribution to NO3− in TSP increased to 50%. The PSCF analysis indicated that external input areas were predominantly from central Henan Province, northern Hubei Province, and central Shaanxi Province. This study quantitatively analyzed the sources of NO3− in atmospheric particulate matter in water sources for the first time, indicating that controlling the emissions of nitrogen oxides from gasoline cars, heavy-duty diesel trucks, and ships could help alleviate haze pollution and enhance air quality in the Danjiangkou reservoir area.

Your personal choices in transportation and food are important for lowering carbon emissions

There is a global need to reduce greenhouse gas emissions to limit the extent of climate change. A better understanding of how our own activities and lifestyle influence our energy use and carbon emissions can help us enable changes in activities that can lead to reductions in carbon emissions. Here we discuss an approach based on examining carbon emissions from the perspective of the unit C, where 1 C is the CO2 from food a person would on average eat every day. This approach shows that total CO2 emissions in China, normalized by the population, is 22.5 C while carbon emissions for a person in the US is 43.9 C. A better appreciation of our own energy use can be obtained by calculating carbon emissions from our own activities in units of C, for example for driving a car gasoline or electric vehicle a certain number of kilometers, using electricity for our homes, and eating different foods. With this information, we can see how our carbon emissions compare to national averages in different countries and make decisions that could lower our personal CO2 emissions.

Evaluation of the point sampling method and inter-comparison of remote emission sensing systems for screening real-world car emissions

Emissions from internal combustion vehicles are currently not properly monitored throughout their life cycle. Remote emission sensing (RES) is a technology that can measure emissions under real driving conditions without contact. Current light extinction based RES systems are capable of providing emission factors for various gases, but lack accuracy for particulate matter (PM). Point Sampling (PS) is an extraction-based RES technique that can measure gases as well as various particle metrics such as black carbon or particle number. In this work, we evaluated the performance of a recently developed PS system and the state-of-the-art light extinction based remote sensing devices EDAR (HEAT) and ORSD (OPUS RSE) during co-location measurements. Validation measurements with portable emission measurement systems and emissions screening of several thousand cars in three European cities provide detailed insights into system's performance. Meteorological evaluations showed that the PS capture rate is strongly influenced by wind, but no other weather influences were found. Both light extinction based systems are unable to measure during rain. We found that all three systems tested were capable of screening NOx emissions from pre-Euro 6 diesel cars. Measurement results show the ability of the PS system to quantify high and low PM emitters equally well. The open-path RES systems (EDAR, ORSD) are capable of estimating PM emissions from pre-Euro 5 diesel cars. However, deficiencies of open-path RES systems are evident in the quantification of PM emissions from newer engine technologies (diesel Euro 5 and beyond) and from petrol cars. The PS system has a 2 to 5 times lower capture rate than open-path RES systems, but the PS measurement results are more accurate (more than 5 times for PM and more than 1.35 times for NOx). The good accuracy of individual measurements makes PS a powerful tool for reliable high emitter identification.

ИССЛЕДОВАНИЕ ФИЗИКО-ХИМИЧЕСКИХ И ПРОТИВОИЗНОСНЫХ СВОЙСТВ МОТОРНЫХ МАСЕЛ ПО ЗАВЕРШЕНИИ ПРОЦЕССА ЭКСПЛУАТАЦИИ

There is given the study of viscous properties of engine oil, depending on the temperature before and after change on modern domestic gasoline and diesel cars, the determination of spectral characteristics and X-ray fluorescence analysis of wear particles after mileage. The degree of viscosity of semi-synthetic oils of two types is estimated. The oils were cooled and heated up to 150 °C. A digital viscometer was used, the dynamic viscosity of all oils decreased with increasing temperature, which is associated with oxidation in waste oil. To assess the effect of motor oil on engine operation, IR spectrometric analysis is performed and the thickness of the lubricating film is determined. The test results showed a qualitative and quantitative change in the characteristic frequencies of the new engine oil and the spent one after 10,000 km. X-ray fluorescence analysis makes it possible to analyze wear products and determine which mechanism in the engine is most susceptible to wear. Lines have characteristic absorption frequencies and indicate a change in physico-chemical properties of oil in the engine. An increase in contamination and in the viscosity of used oils is associated with the presence of impurities formed during the oxidation and polymerization of the base oil. It is necessary to increase the number of samples and sampling during different periods of operation so that you can verify the same effect throughout the entire engine operation. The results obtained indicate that these methods can be used to analyze and control the mode of operation of oils in the engine, allowing to determine the wear and further apply appropriate additives to the oil to improve performance properties.

Towards zero pollution vehicles by advanced fuels and exhaust aftertreatment technologies

Vehicular emissions deteriorate air quality in urban areas notably. The aim of this study was to conduct an in-depth characterization of gaseous and particle emissions, and their potential to form secondary aerosol emissions, of the cars meeting the most recent emission Euro 6d standards, and to investigate the impact of fuel as well as engine and aftertreatment technologies on pollutants at warm and cold ambient temperatures. Studied vehicles were a diesel car with a diesel particulate filter (DPF), two gasoline cars (with and without a gasoline particulate filter (GPF)), and a car using compressed natural gas (CNG). The impact of fuel aromatic content was examined for the diesel car and the gasoline car without the GPF. The results showed that the utilization of exhaust particulate filter was important both in diesel and gasoline cars. The gasoline car without the GPF emitted relatively high concentrations of particles compared to the other technologies but the implementation of the GPF decreased particle emissions, and the potential to form secondary aerosols in atmospheric processes. The diesel car equipped with the DPF emitted low particle number concentrations except during the DPF regeneration events. Aromatic-free gasoline and diesel fuel efficiently reduced exhaust particles. Since the renewal of vehicle fleet is a relatively slow process, changing the fuel composition can be seen as a faster way to affect traffic emissions.

Emission performance evaluation of urban passenger car fleet through field investigation data in a megacity.

Continued improvements in living standards and the economic well-being in the megacities have led to a huge surge in vehicular density. The worst environmental outcome of the same has been persistent unsafe urban air quality, thanks to vehicular emission. Further, the existing inspection and maintenance programs, conceived to check such emission remain largely ineffective, particularly in developing countries. This is due to the absence of a thorough assessment of the vehicle's compliance with the in-use emission norms generated through reliable field investigation data. To address this gap, the present comprehensive study collected real-time tailpipe emission data from 2040 cars in Delhi, India. Exhaust emission parameters, namely, CO (carbon monoxide), HC (hydrocarbon), and SE (smoke emission), were recorded from both petrol and diesel-driven cars of private ownership, in collaboration with the emission compliance test centers. The performance of cars was assessed in terms of their compliance with the in-use BS (Bharat Stage) emission norms. The one-of-its-kind study reported the petrol cars to be highly compliant toward the BS IV norm while faring even better toward BS II for both CO and HC emissions (80-90%). The conformance to the HC norm was found to be typically better than that for CO (85-90% versus 75-80%). For the diesel-driven cars, BS III compliance levels were reported relatively better compared to BS IV (90% in the case of the former against 80% in the latter's case). Further, the study puts forward a clear indication that the in-use emission norm and maintenance status of cars have a direct and negative relationship with tailpipe emission parameters. Cars of both overseas and domestic origin have almost equal degrees of compliance with the emission norms (over 80% in any case). The study recommends the incorporation of these two critical vehicular variables, i.e., maintenance status and in-use emission standard in the emission certification policy.

Healing patient, harming planet? A drive towards sustainable surgery: review of waste production and recyclability of surgical instrument packaging.

Healthcare contributes more than 1% of all domestic waste in the United Kingdom (UK), with operating theatre waste alone accounting for approximately 50% of all hospital waste. In November 2022, the UK Surgical Royal Colleges issued an Intercollegiate Climate Emergency Declaration and called for urgent action. We review waste production and the recyclability of surgical instrument packaging used in a common ear, nose and throat procedure (thyroidectomy) and suggest strategies to make this surgery more sustainable,. These strategies can be generalised to other surgeries. We prospectively audited packaging waste from 20 thyroidectomies performed at the Royal Marsden Hospital in the UK between July and December 2022. All packaging was weighed, categorised and analysed after the operation. On average, each thyroidectomy produced packaging waste comprising 183g (34%) of plain paper/cardboard, 167g (31%) of soft plastic film, 142g (26%) of laminated paper, 37g (7%) of hard plastic and 11g (2%) of metal foil. Of all the packaging collected, only one item had a recycling label. When extrapolated to the 7,851 thyroidectomies performed in the National Health Service during the fiscal year 2021/2022, the estimated total weight of packaging waste would be 4.2 tonnes, of which only 31.4kg would be indicated as recyclable. When converted to an estimated carbon footprint, total carbon emissions would be 1,048kg CO2e, equivalent to three round trips from London to Edinburgh in a petrol car. This audit demonstrates the different categories and vast amount of packaging waste from a common operation. Manufacturers should place clear recyclability labels on packaging, and switch to recyclable materials and a digital information booklet where possible. Local waste audit and analysis can be simple first steps towards making surgery more sustainable.

Why People Prefer Petrol Cars Over Electric Cars

bstract: This research paper aims to explore and understand the reasons behind people's continued preference for petrol cars over electric cars. Despite the global push towards sustainable and environmentally friendly transportation, the adoption of electric cars remains relatively low compared to their petrol counterparts. Through a thorough examination of various factors including cost, infrastructure, range anxiety, performance, and environmental perceptions, this research paper examines the underlying reasons for this preference.

Molecular composition of fresh and aged aerosols from residential wood combustion and gasoline car with modern emission mitigation technology.

Emissions from road traffic and residential heating contribute to urban air pollution. Advances in emission reduction technologies may alter the composition of emissions and affect their fate during atmospheric processing. Here, emissions of a gasoline car and a wood stove, both equipped with modern emission mitigation technology, were photochemically aged in an oxidation flow reactor to the equivalent of one to five days of photochemical aging. Fresh and aged exhausts were analyzed by ultrahigh resolution mass spectrometry. The gasoline car equipped with a three-way catalyst and a gasoline particle filter emitted minor primary fine particulate matter (PM2.5), but aging led to formation of particulate low-volatile, oxygenated and highly nitrogen-containing compounds, formed from volatile organic compounds (VOCs) and gases incl. NOx, SO2, and NH3. Reduction of the particle concentration was also observed for the application of an electrostatic precipitator with residential wood combustion but with no significant effect on the chemical composition of PM2.5. Comparing the effect of short and medium photochemical exposures on PM2.5 of both emission sources indicates a similar trend for formation of new organic compounds with increased carbon oxidation state and nitrogen content. The overall bulk compositions of the studied emission exhausts became more similar by aging, with many newly formed elemental compositions being shared. However, the presence of particulate matter in wood combustion results in differences in the molecular properties of secondary particles, as some compounds were preserved during aging.

Present and Future Trends of Electric Vehicles in India

The electric vehicles market in India is making significant progress in terms of environmental sustainability. Various new car companies are revolutionizing the industry by introducing innovative models. The interest in electric vehicles is rapidly growing, and with the introduction of new pricing models, the market is expected to expand even further. Recognizing this shift, existing car manufacturers are striving to unveil new hybrid or electric vehicle models. Developed countries such as the UK and France have already announced plans to ban the sale of diesel and petrol cars by 2040. Experts predict that Europe will witness a complete transition to electric vehicles five years prior to the deadline. This transformation has led to increased commitments and competition among leading car manufacturers and businesses in the automotive industry. Norway, for instance, is experiencing remarkable progress in the electric vehicles market, with nearly 30% of new car sales in December 2017 being electric battery-powered vehicles. Energy experts anticipate that China and India will drive the demand for electric vehicles, as these countries prioritize the development of low-carbon emission transportation solutions. In response to the growing industry, many companies are planning to introduce electric vehicle charging points to support the increasing demand for electric vehicles.

Mobile monitoring reveals the importance of non-vehicular particulate matter sources in London.

This study uses mobile monitoring to gain a better understanding of particulate matter (PM) sources in two areas of Central and Outer London, UK. We find that, unlike emissions of nitrogen oxides (NO + NO2 = NOx), which are elevated in Central London due to the high number of diesel vehicles and congestion, fine particulate matter (PM2.5) emissions are well-controlled. This finding provides evidence for the effectiveness of vehicle particulate filters, supporting the view that their widespread adoption has mitigated PM2.5 emissions, even in the highly dieselized area of Central London. However, mobile monitoring also reveals infrequent elevated PM2.5 concentrations caused by malfunctioning vehicles. These events were confirmed through simultaneous measurements of PM2.5 and sulfur dioxide (SO2), the latter being a strong tracer of engine lubricant combustion. A single event from a gasoline car, representing just 0.15% of the driving distance in Outer London, was responsible for 7.4% of the ΔPM2.5 concentration above background levels, highlighting the ongoing importance of addressing high-emission vehicles. In a novel application of mobile monitoring, we demonstrate the ability to identify and quantify non-vehicular sources of PM. Among the sources unambiguously identified are construction activities, which result in elevated concentrations of coarse particulate matter (PMcoarse = PM10 - PM2.5). The mobile measurements clearly highlight the spatial extent of the influence of such sources, which would otherwise be difficult to determine. Furthermore, these sources are shown to be weather-dependent, with PMcoarse concentrations reduced by 62.1% during wet conditions compared to dry ones.

Bambusa tulda: A potential feedstock for bioethanol and its blending effects on the performance of spark ignition engine

Alternatives to conventional fuel sources must be investigated due to strict regulatory requirements and the depletion of fossil fuel supplies. As a result, of better transportation and population growth, the requirement for energy is increasing daily. Bioethanol may be used successfully to replace both gasoline and spark ignition engine diesel. Most nations blend 10% bioethanol with gasoline in automobiles. Several nations, notably India, have announced that they will soon begin blending 20% bioethanol with gasoline. Bambusa Tulda is used as a raw material for the extraction of bioethanol, which is a type of Indian bamboo. This study covers both the ethanol extraction from bamboo and the effects of various mixtures on spark-ignited engine performance. Four separate blends were developed on a volumetric basis at varying engine speeds, and the wide-open throttle was utilized to evaluate the performance and emissions of each mix with a constant compression ratio of 10:1. When bioethanol was enhanced, combustion efficiency, indicated power, engine power, mechanical efficiency, and volumetric efficiency all increased. Hydrocarbon, carbon monoxide, and carbon dioxide emissions decreased, while nitrogen oxide emissions increased. The engine performance of BE 15 was found to be the greatest among all the gasoline blends tested. According to this study, when nitrogen oxide emission control methods are applied, bamboo may be used as a feedstock for the manufacture of second-generation bioethanol. This invention offers a bioethanol production process that is good for environmental sustainability.

Predictors of electric vehicle adoption intent in rideshare drivers relative to commuters

Research examining electric vehicle (EV) adoption intent is growing, but neglects rideshare drivers (e.g., Uber & Lyft), who drive up to 13% of all miles driven in metropolitan areas. This study uses Noppers’ framework on sustainable innovation adoption to compare rideshare drivers to commuters on symbolic and instrumental attribute (e.g., costs, maintenance) perceptions, and their influences on EV adoption intent. It is possible that rideshare drivers have stronger symbolic attribute ratings than commuters because more people see their vehicles for extended periods of time, so what the vehicle signals about drivers may be more salient to drivers; alternatively, because rideshare drivers use their vehicles for work, drivers may perceive vehicles in primarily instrumental terms. We test these competing hypotheses using a survey of 136 rideshare drivers and 378 commuters. Relative to commuters, rideshare drivers rated symbolic attributes higher and EV maintenance costs somewhat more favorably, but significantly fewer had access to a charging spot. A regression model found that both instrumental and symbolic attributes positively predicted EV adoption intent for both groups. Relative to commuters, symbolic attributes were weaker predictors of EV adoption intent among rideshare drivers, whereas instrumental attributes, particularly perceptions that the purchase cost of an EV was lower than that of a gasoline car, were stronger.

Research on Tesla's Localization Strategy Development in China

Tesla Inc. has been continuously pushing the global automobile industry towards a more environmentally-friendly, smarter direction, the majority of the public believe that Tesla wanted new forces to help it fight against the traditional gasoline car manufacturers. And Tesla has shown its great localization strategy in China, there are multiple factors that contribute to its success, such as setting up the gigafactory in Shanghai, fully considering consumer demand, implementing successful market strategy and applying industry-leading technologies and safety. This research focused on Tesla Inc.'s history in China and the current market condition, intended to delve deep into Tesla's localization in the China market and offered a more comprehensive understanding about Tesla's market and localization strategy. Specifically, this paper explored how Tesla leverages its global influence to affect the China electric vehicle market and compared it with the current study in order to provide a more multi-dimensional perspective to understand the characteristics of Tesla in China, thus providing reference for the development electric vehicle market, and providing a strong base for future research.

Experimental and CFD analysis on the impact of hydrogen as fuel on the behavior of a passenger car gasoline direct injection engine

The influence of hydrogen induction on the behavior of a Multi cylinder automotive GDI (Gasoline Direct Injection) engine was studied. An advanced 3D engine simulation was done and validated with experimentally acquired 5% and 10% hydrogen mass coupled with gasoline direct injection. Comparing to the pure gasoline mode, introducing hydrogen showed considerable improvement in engine's BTE (brake thermal efficiency) at all power outputs. The maximum BTE was observed as 27.2%, 30% and 32.5 respectively with pure gasoline, 5% and 10% hydrogen mass shares at the engine's power output of 21 kW. At all power outputs, hydrogen admission was shown to produce a smaller amount hydrocarbon (HC) and carbon monoxide (CO) emissions than pure gasoline operation. At 21 kW engine power the HC was noted as 3360, 2400 and 2050 ppm respectively with Pure Gasoline, 5% and 10% hydrogen mass shares. CFD results on the HC and CO emissions indicated a strong agreement with the experimental results. NOx emission was noted as higher with hydrogen addition (80 and 100 ppm respectively with 5% and 10% hydrogen mass shares) as compared to 60 ppm with pure gasoline mode. High temperature of the gas supported by the CFD due to the rapid combustion of hydrogen was noted as the reason for the higher NOx emissions with hydrogen addition. CFD results on cylinder pressure and HRR matched very well with the experimental results. A small amount of hydrogen added to the gasoline as a fuel supplement might greatly improve BTE while lowering HC and CO emissions. The recommended optimum hydrogen mass share is 10% for the best performance of the above said engine without any modification in engine design.

Studies on Engine Oil Degradation Characteristics in a Field Test with Passenger Cars

Nowadays, a car’s engine oil change interval is an essential factor in reducing wear. The correct choice depends on various factors. This study analyzes the changes in the composition of three different engine oils (0W30, 5W30, and 5W40) during the generally accepted oil change interval (15,000 km) in gasoline and diesel cars during the post-warranty period. Commercially available low-level biofuel blends (B7 and E10) were used to power test vehicles in a field test. Engine oil samples were taken every 3000 km for more detailed analysis and tested in an accredited laboratory. The contaminants in the engine oil were determined using several testing methods: spectrometric analysis, gas chromatography, etc. Studies have shown that all used cars have an increase in the number of iron particles, an increased concentration of silicon, and also an increase in the number of nickel particles above 12,000 km. Tests also showed a sharp drop of molybdenum anti-friction additives 4.5 times and a gradual increase in fuel concentration for the Opel Insignia over 12,000 km, but over 9000 km, a significant increase in the concentration of chromium particles. Based on this research results, it is preferable to choose a maintenance interval of no more than 12,000 km for cars during the post-warranty period. In this way, the intensity of engine wear can be reduced due to the loss of adequate protective properties of the engine oil.

The effects of higher bioethanol blends on greenhouse gas emissions from the UK passenger car fleet at various time horizons during the transition to net zero: A review

There is a need to minimise the Greenhouse Gas Emissions (GHG) of petrol-powered cars during the transition to net zero. This research examines the effects on GHG from the recent adoption of E10 as the standard 95-octane petrol grade in the United Kingdom (UK). Also, it considers the potential of using higher bioethanol blends within the national car fleet and the effect of increased lifetime mileage due to the growing incidence of extended vehicle ownership. A comprehensive fleet turnover model and a separate numerical model to predict the GHG emissions for various powertrain types using different bioethanol blends were developed. Sensitivity studies that model the effects of different annual mileage using E10 and applying the proposed UK fleet composition scenarios at 10-year intervals from 2020 to 2050 were conducted. The results support the claimed percentage reduction of GHG emissions arising from the UK petrol car fleet using E10 when compared to E5 and establish that using a higher bioethanol blend such as E15 would provide still further reductions in most instances except in the case of plug-in hybrid vehicles where an increase in GHG emissions was observed at the 2030 and 2040 time horizons. An increase in annual mileage creates a linear increase in GHG emissions, although the rate of increase is not the same for each propulsion type. Such an increase can potentially disrupt the achievement of the UK's 2050 net zero target and future periodic carbon budgets.

Holistic analysis of consumer energy decarbonisation options and tariff effects

The consumers' perspective on low-carbon technologies is critical to decarbonise their emissions, the effect from the array of modern tariff structures and the dramatic variation in tariff rates on the technology viability is yet to be realised. Here we present a comprehensive holistic approach that includes electrification and hydrogen options to understand the trade-offs in technologies and tariffs for consumers in their energy decarbonisation which is missing from the technology specific analysis in the literature. The novel framework considers all consumer demands simultaneously through combinations of different low-carbon technologies over a 20-year lifetime, linked with conventional and emerging electricity tariff structures. Using the UK as a case study, we found that electrification is more cost-effective than hydrogen for most consumers to reduce their energy emissions and that the lowest 20-year low-carbon solution of air source heat pump, electric vehicle, and photovoltaics may have slightly (9%) higher lifetime cost to the gas boiler and petrol car baseline but can achieve 54% emission reduction using the grid electricity mix and energy tariffs in 2020. In terms of technologies, electric vehicles and solar photovoltaics are the only evaluated technologies that have the potential to reduce customer's energy costs, 8% and 0.2% respectively, alongside emissions reductions, of 28% and 2% respectively. Energy storage technologies, though significantly benefit the grid by unlocking demand-side flexibility, were not economic beneficial to customers until the tariff increase due to the energy crisis. Designing the average day rate of a tariff is most important for adopting electrified heating, on the other hand energy storage use requires low off-peak rates, where we quantified the minimum required difference in tariff peak to off-peak rates to allow energy storage financial justification. This learning can be used to help incentivise consumers to adopt these technologies, allowing greater system benefits.

A COMPREHENSIVE ANALYSIS OF ISOLATED AND NON-ISOLATED CONVERTER TOPOLOGIES AND FAST CHARGING TECHNOLOGIES FOR HYBRID ELECTRIC VEHICLES

Electric vehicles (EVs) are a promising solution for future transportation systems due to their significant role in reducing carbon emissions, making them a central focus of research and development efforts. One crucial aspect of EVs is rapid charging technology, which aims to deliver refuelling experiences comparable to traditional gasoline cars. This article delves into the current state of electric vehicle charging infrastructure, with a particular emphasis on the importance of rapid charging technology to meet the present and future refuelling demands of EVs. It presents a comparative analysis of different DC-DC converter topologies for both battery electric and plug-in hybrid vehicles, considering factors such as performance, output power, current and voltage ripples, conduction loss, recovery loss, switching frequency loss, reliability, durability, and cost. Additionally, the article explores the architecture, advantages, and disadvantages of AC-DC and DC-DC converter topologies for rapid charging stations. Moreover, the study addresses critical issues and challenges associated with direct current rapid charging in electric vehicles. Finally, the article offers valuable technical insights and contributions to the ongoing development of electric vehicle systems. In essence, this article highlights the environmental benefits of electric vehicles and their growing popularity, emphasizing the need for advanced rapid charging technology while providing a comprehensive analysis of related technologies and challenges. Key Words: Power output, Current fluctuations, Voltage fluctuations, Voltage fluctuations, Conductive losses, Recovery inefficiencies, Switching frequency-related inefficiencies, Dependability, Longevity, Economic considerations, AC-DC converter configurations, DCDC converter designs.

Detecting State of Charge False Reporting Attacks via Reinforcement Learning Approach

The increased push for green transportation has been apparent to address the alarming increase in atmospheric <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${CO}_2$</tex-math> </inline-formula> levels, especially in the last five years. The success and popularity of Electric Vehicles (EVs) have led many carmakers to shift to developing clean cars in the next decade. Moreover, many countries around the globe have set aggressive EV target adoption numbers, with some even aiming to ban gasoline cars by 2050. Unlike their gasoline-based counterparts, EVs comprise many sensors, communication channels, and decision-making components vulnerable to cyberattacks. Hence, the unprecedented demand for EVs requires developing robust defenses against these increasingly sophisticated attacks. In particular, recently proposed cyberattacks demonstrate how malicious owners may mislead EV charging networks by sending false data to unlawfully receive higher charging priorities, congest charging schedules, and steal power. This paper proposes a learning-based detection model that can identify deceptive electric vehicles. The model is trained on an original dataset using real driving traces and a malicious dataset generated from a reinforcement learning agent. The Reinforcement Learning (RL) agent is trained to create intelligent and stealthy attacks that can evade simple detection rules while also giving a malicious EV high charging priority. We evaluate the effectiveness of the generated attacks compared to handcrafted attacks. Moreover, our detection model trained with RL-generated attacks displays greater robustness to intelligent and stealthy attacks.