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The number of electric vehicles is increasing in line with the global carbon reduction targets. More households are installing electric charging points to complement the existing charging infrastructure. The increasing electricity prices affected by the global energy/economic crisis however pushed more households towards coupling their charging points with renewable energy generation and storage systems to manage the supply and demand of energy more effectively. In this study, an electric charging station equipped with Photovoltaic panels and an electric storage system utilising second-life Electric Vehicles (EV) batteries is designed and analysed. Various electricity generation capacities are considered to be installed on the roof of the case study building ranging from 5m2 and 20m2. The second-life batteries are disposed from EVs with an 80% state of health. MATLAB Simulink is used for mathematical modelling of system.

To decarbonize heavy-duty vehicles solely through electrification with batteries is challenging as large batteries are required for a meaningful range, severely impacting payload. Employment of hybrid electric powertrains where fuel cells are integrated with batteries can deliver increased range and payload. However, the energy balance between the fuel cell and the battery needs to be analyzed to optimize the sizing of the powertrain components. This study has performed a multi-objective optimization using genetic algorithm to obtain the optimum range and hydrogen consumption for a DAF 44 tons heavy-duty truck. The proposed truck powertrain has been numerically modelled in AVL CRUISE M software. The electric drive from Involution Technologies Ltd and Bramble Energy Ltd’s printed circuit board fuel cell (PCBFC) are used in the model.

Drive cycles have been the official way to create standardized comparisons of fuel economy and emission levels between vehicles. Since the 1970s these have evolved to be more representative of real-world driving, with today’s standard being the World Harmonized Light Vehicle Testing Procedure. The performance of battery electric vehicles which consist of electric drives, battery, regenerative braking and their management systems may differ when compared to that of vehicles powered by conventional internal combustion engines. However, drive cycles used for evaluating the performance of vehicles, were originally developed for conventional powered vehicles. Moreover, the kinematic parameters that can distinguish the real-world performance of the differently powered vehicles are not fully known. This work aims to investigate the difference between vehicles powered by pure internal combustion engine, electric hybrid and pure electric drive.

Formula (1) vehicles have transitioned from E5 to E10 fuel for the 2022 season to reduce carbon emissions and by 2026 the vehicles are required to use 100% sustainable fuels. The aim of this paper is to identify the operating envelope of the F1 power unit for E10-E100 fuel and the resulting emission levels for these fuel compositions using numerical simulations. To achieve this aim an F1 engine model has been developed in GT-Suite with reference to the FIA 2022 Technical Regulations. The combustion model has been validated using data obtained from literature relating to laminar and turbulent flame speed, friction and heat transfer characteristics within the combustion chamber. One of the main challenges of using ethanol-based fuels is the increased levels of formaldehyde in the tailpipe.

Electrification is one of the main solutions for the decarbonization of the transport system. It is employed widely by the automotive industry in light- and medium-duty vehicles and recently started to be considered in heavy-duty applications. However, powertrain electrification of heavy-duty vehicles, especially for Class 8 trucks, is very challenging. In this study, the battery-electric powertrain energy and technical performance of a DAF 44 tones truck are compared for two different electric drives. The case study truck is modeled in AVL CRUISE M software and the battery electric powertrain is evaluated for long haul driving cycle. The minimum number of battery packs is determined by defining the lowest energy consumption of the powertrain designed for the proposed drive cycle. Also, a transient analysis is accomplished to investigate the impact of various electric drives on energy consumption and performance of the proposed electric powertrain.

Small diesel engines are a common primer for micro and mini-grid systems, which can supply affordable electricity to rural and remote areas, especially in developing countries. These diesel generators have no exhaust after-treatment system thus exhaust emissions are high. This paper investigates the potential of introducing simulated synthetic gas (syngas) to diesel in a small diesel engine to explore the opportunities of widening fuel choices and reducing emissions using a 5.7kW single cylinder direct injection diesel generator engine. Three different simulated syngas blends (with varying hydrogen content) were prepared to represent the typical syngas compositions produced from downdraft gasification and were injected into the air inlet. In-cylinder pressure, ignition delay, premixed combustion, combustion stability, specific energy consumption (SEC), and gaseous and particle emissions were measured at various power settings and mixing ratios.

Formula One (F1) is considered to be the forefront of innovation for the automotive and motorsport industry. One of the key provisions has been towards the inclusion of the Energy Recovery System (ERS) since 2014 in F1 regulations. ERS comprises Motor Generator Unit-Heat (MGU-H), Motor Generator Unit-Kinetic (MGU-K) and an Energy Storage (ES). This has not only converted the conventional powertrain into a hybrid power-split device, but also imposed constraints on the fuel energy available, energy recovered and deployed by MGU-K, and charge stored in ES, along with various other parameters. Although the objective for a F1 race is to minimize lap-time, it is obvious that there is no unique control path or decision to meet this objective. This builds up needs to optimally control the power-split and energy of the system.

The COVID-19 pandemic has forced governments to implement rigorous containment measures on reduction or cessation of human mobility, transportation and economic activities, to control the spread of the virus. This is considered as a unique opportunity to study the impact of local lockdowns periods, especially, on the vehicle emission levels, and urban air quality in cities with high pollution levels, such as Bogota, Colombia. The first case was confirmed in Colombia on March 6, 2020, since then to prevent its propagation, the government declared a national lockdown starting from March 20 until August 31, 2020. Therefore, this study attempted to analyse the air quality in Bogota by assessing the concentrations of the atmospheric pollutants NO₂, SO₂, O₃, CO, PM₂.₅ and PM₁₀ during the lockdown period and the corresponding concentrations levels during the same period in 2018 and 2019. The data for this pilot study was obtained from the air quality monitoring stations of Bogota.

Electric Vehicles (EVs) are considered to be a worthy alternative to automobiles powered by internal combustion engines to achieve the goal of sustainable transportation. For their many known advantages, Li-ion cells are considered to be the most practical energy storage solution for the purpose of EVs propulsion currently. The capability of Li-ion cells to store energy in extreme cold operating temperatures is significantly lower than that at nominal operating temperatures due to greater power losses at cold temperatures. Therefore, it leads to degradation of performance of EVs in sub-zero temperatures. The present work proposes a novel approach to use numerical simulation technique to build an EV model based on BMW i3 using GT Suite at sub-zero temperatures. The model is validated against experimental data obtained from Argonne National Laboratory for US06, HWY and UDDS legislative drive cycles.

Formula 1 has always played a major role in technological advancements within the automotive and motorsport sectors. The adaptive changes introduced for the Power Unit (PU) in 2014 forced constructors, in collaboration with industry partners, to invent technologies for exceeding 50% brake thermal efficiency within a short span of time, demonstrating that technology-forcing regulations through motorsport is the favorable route to achieve transformative changes within the automotive sector. Therefore, in an attempt to address arising global warming and health concerns, the present work analytically examines the ambient air quality in track stadia during F1 race events to identify potential PU exhaust emission targets. It models the volume of air contained within the circuits located near heavily built-up areas assuming stagnant air conditions and uniform mixing.

This study analyzes the performance of the Energy Recovery System (ERS) of a Formula One car (F1) based on the qualification performance of 19 drivers for the first calendar race of the 2019 FIA Formula One World Championship®. In this study, the race circuit analysed was split into different sectors to examine the energy transfer between the Motor Generator Unit-Kinetic (MGU-K) and the Energy Storage (ES) systems. Positive Kinetic Energy (PKE) concept was used for estimating the energy deployment potential of the ERS along with numerical simulations for estimating the energy recovering potential. This investigation highlights the strategies used by different drivers and the effect of driver to driver variation on their ERS performance during qualification. The methodology demonstrated in this study is able to identify the correlation between the unique driving style of individual drivers and the ERS strategies used by the teams for maximizing the performance of their car.

A Gas to liquid (GTL) fuel was investigated for its combustion and emission performance in an IVECO EURO5 DI diesel engine with a DOC (Diesel Oxidation Catalyst) and DPF (Diesel Particle Filter) installed. The composition of the GTL fuel was analyzed by GC-MS (gas chromatography-mass spectrometry) and showed the carbon distribution of 8-20. Selected physical properties such as density and distillation were measured. The GTL fuel was blended with standard fossil diesel fuel by ratios of diesel/GTL: 100/0, 70/30, 50/50, 30/70 and 0/100. The engine was equipped with a pressure transducer and crank angle encoder in one of its cylinders. The properties of ignition delay and maximum in-cylinder pressure were studied as a function of fraction of the GTL fuel. Particle emissions were measured using DMS500 particle size instrument at both upstream (engine out) and downstream of the DPF (DPF out) for particle number concentrations and size distribution from 5 nm to 1000 nm.

Heat Release Rate (HRR) analysis is indispensable in engine research. The HRR of Internal Combustion Engines (ICEs) is most sensitive to gamma (γ). The proposed HRR models in literature were largely based on γ expressed as functions of temperature. However, γ is depended on temperature as well as the excess air ratio (λ). In this work, an improved HRR model based on γ(T, λ) was used to investigate the combustion behaviour of standard diesel, Gas-to-Liquid (GTL) diesel and Hydrotreated Vegetable Oil (HVO) diesel in a 96 kW, multiple fuel injection, Euro V, Direct Injection (DI) engine. The improved HRR model (Leeds HRR model) was validated for the alternative fuels by comparing the fuel masses predicted by the model to the measured fuel masses. The fuel masses predicted by the Leeds HRR model were also compared to the predictions from four HRR models that were based on γ(T).

The search for alternative fuel for transport vehicles and also replacement of internal combustion engines in order to reduce the harmful emissions have been forcing the vehicle manufacturers to innovate new technology solutions for meeting the stringent legislative targets. Mexico’s commitment for de-carbonisation of transport sector and meeting the environmental goals is shaping it especially, and with this, it favours the move towards electrification of the vehicles. The aim of the present work is to numerically evaluate the possibility of replacing the IC engine in the existing hybrid vehicles with the Hydrogen fuel cell system. This work modelled a Hydrogen fuel cell vehicle based on Toyota MIRAI and validated the fuel economy performance of the vehicle using experimental data. This validated model was used to estimate the fuel economy for real-world drive cycles generated in 2019 from Mexico City.

Autonomous vehicles in formula student competition is a relatively new competition, with most of the teams testing new concepts every year with their challenger for the season. A background search conducted reflects the various concept changes offered by the FS teams in Formula student Germany each year. Hence, it can be concluded that the teams are uncertain about many concepts in an autonomous vehicle. This paper explores one such aspect; the choice of controller governs the steering capabilities of the autonomous vehicle. An MPC controller is used to build a basic controller model for the autonomous vehicle in the formula student competition. A bicycle model representative of the Oxford Brookes Racing team's electric vehicle is modeled, and the MPC controller is used to check various vehicle dynamic parameters in Simulink.

Due to the variability of real traffic conditions for vehicle testing, real-world vehicle performance estimation using simulation method become vital. Especially for heavy duty vehicles (e.g. 40 t trucks), which are used for international freight transport, real-world tests are difficult, complex and expensive. Vehicle simulations use mathematical methods or commercial software, which take given driving cycles as inputs. However, the road situations in real driving are different from the driving cycles, whose speed profiles are obtained under specific conditions. In this paper, a real-world vehicle performance estimation method using simulation was proposed, also it took traffic and real road situations into consideration, which made it possible to investigate the performance of vehicles operating on any roads and traffic conditions. The proposed approach is applicable to all kind of road vehicles, e.g. trucks, buses, etc. In the method, the real-road network includes road elevation.

The aim of the present work is to propose a control strategy for maximizing the performance of a Formula One (F1) car through numerical simulation for 2021 regulations taking 2019 regulations as a benchmark. This study has developed an engine-powertrain model of an F1 car with real world driver data for estimating the vehicle’s full throttle performance. The maximum possible energy recovered, stored and deployed by the Energy Recovery System (ERS) was estimated for the first 10 circuits in the 2019 FIA Formula One World Championship® Race Calendar. A 1.6L V6 Internal Combustion Engine (ICE), as well as, a full vehicle was modelled according to the 2019 Federation Internationale de l'Automobile (FIA) Formula One technical regulations using GT-Suite software. The model was validated against the experimental data. The data for validation was extracted from On- Board videos using Optical Character Recognition (OCR) and FIA regulations.

Light-duty China-6, which is among the most stringent vehicle exhaust emission standards globally, mandates the monitoring and reporting of real driving emissions (RDE) from July, 2023. In the process of regulation promulgation and verification, more than 300 RDE tests have been performed on over 50 China-5 and China-6 certified models. This technical paper endeavors to summarize the experience of RDE practice in China, and discuss the impacts of some boundary conditions (including vehicle dynamic parameters, data processing methods, hybrid propulsion and testing altitude) on the result of RDE measurement. In general, gasoline passenger cars confront few challenges to meet the upcoming RDE NOx requirement, but some China-5 certified samples, even powered by naturally-aspirated engines may have PN issues. PN emissions from some GDI-hybrid powertrain systems also need further reduction to meet China-6 RDE requirements.

Air pollution levels in an urban environment is a major concern for developed and developing countries alike. Governments around the world are constantly trying to control and reduce air pollution levels through regulations. Low emission zones are being designated in cities worldwide in order to reduce the level of pollutants in big cities. The automotive industry is affected by those regulations and they are becoming more demanding over the years. Present work is aimed at developing a control strategy for a hybrid vehicle in order to optimize the fuel economy and emission levels based on GPS information, driver specific driving characteristics and weather forecast data for a given route. It uses powertrain model of a hybrid vehicle for developing route and driver specific control strategy. The full vehicle model has two sub-models: a route selector and a powertrain optimization model.

Hydrogenated Vegetable Oil (HVO) diesel fuels have the potential to provide a reduced carbon footprint for diesel engines and reduce exhaust emissions. Therefore, it is a strong candidate for transport and diesel powered machines including electricity generators and other off-road machines. In this research, a waste cooking oil derived HVO diesel was investigated for its combustion and emission performance including ignition delays, size segregated particulate number emissions and gaseous emissions. The results were compared to the standard petroleum diesel. A EURO5 emission compliant three litre, direct injection, intercooled IVECO diesel engine equipped with EGR was used which has a maximum power output of 96kW. The engine was equipped with an integrated DOC and DPF aftertreatment system. Both the upstream and downstream of the aftertreatment emissions were measured. The tests were conducted at different RPM and loads at steady state conditions.