Assessing the Sustainability of Electric and Hybrid Buses: A Life Cycle Assessment Approach to Energy Consumption in Usage

Abstract

The global adoption of battery electric vehicles (EVs) and hybrid electric vehicles (HEVs) as a substitute for internal combustion engine cars (ICEs) in various nations offers a substantial opportunity to reduce carbon dioxide (CO₂) emissions from land transportation. EVs are fitted with an energy conversion system that efficiently converts stored energy into propulsion, referred to as “tank-to-wheel (TTW) conversion”. Battery-electric vehicles have a significant advantage in that their exhaust system does not produce any pollutants. This hypothesis is equally relevant to public transport. Despite their higher upfront cost, electric buses contribute significantly to environmental sustainability during their operation. This study aimed to evaluate the environmental sustainability of electric buses during their operational phase by utilizing the life cycle assessment (LCA) technique. This paper used the MATLAB R2021b code to ascertain the mean load of the buses during their operation. The energy consumption of battery electric and hybrid electric buses was evaluated using the WLTP Class 2 standard, which refers to vehicles with a power-to-mass ratio between 22 and 34 W/kg, overing four speed phases (low, medium, high, extra high) with speeds up to 131.3 km/h. The code was used to calculate the energy consumption levels for the complete test cycle. The code adopts an idealized rectangular blind box model, disregarding the intricate design of contemporary buses to streamline the computational procedure. Simulating realistic test periods of 1800 s resulted in an average consumption of 1.451 kWh per km for electric buses and an average of 25.3 L per 100 km for hybrid buses. Finally, through an examination of the structure of the Hungarian power system utilization, it was demonstrated that electrification is a more appropriate method for achieving the emission reduction goals during the utilization phase.

1. Introduction

When businesses and society progress, an increasing number of individuals become cognizant of the alterations occurring with climate and environmental obstacles. Transportation emissions are continuously making a substantial contribution to world levels of greenhouse gases. As the continuous expansion of battery production capacity as well as the layout of various types of infrastructure and the support of relevant government policies, pure electrification of the transportation field has become the future trend in various countries and regions. Take the Hungarian market as an example; the competitive labor cost has led many multinational battery manufacturers, including BYD, CATL, and LG, to establish new battery facilities here and give support services to various car manufacturers in the EU [1]. The electric vehicles often referred to as “zero-emission” typically focus only on the emissions during the use phase, or the “tank-to-wheel” aspect in life cycle assessment. However, when the full life cycle—production, usage, and recycling—is taken into account, an electric vehicle’s overall carbon footprint may not necessarily be lower than a conventional internal combustion engine vehicle (ICE) [2]. With the number of electric vehicles increasing, this issue is becoming more evident. Once a power battery nears the end of its intended lifespan, it is frequently recycled separately or reused for secondary purposes such as energy storage, and these operations can be expensive.

To achieve the sustainable growth of the policy-driven BEV sector [3], especially electric buses, it is necessary to tackle many sustainability concerns. BEV technology has significant challenges at both the national and industrial levels, including insufficient infrastructure, expensive power batteries, limited range, and poor customer interest in purchasing. The industry is confronted with challenges, such as excessive expenditure, sluggish advancements in fundamental battery technology, and poor market demand. Consequently, several automakers are reducing or modifying their electrification objectives. Policymakers must evaluate new energy vehicles not just from an economic standpoint, but also from an environmental and social perspective in order to guarantee the long-term viability of the sector after policy implementation and to avoid problems, like over production capacity.

Ensuring sustainability in both product and technology aspects might present distinct difficulties. Companies with diverse interests choose electric drive technologies, such as plug-in hybrid electric cars (PHEVs), battery electric vehicles, or fuel cell vehicles (FCVs), depending on their compatibility with local supply chains and customer preferences [4]. There are issues about how suppliers and manufacturers may effectively promote ecologically and socially responsible practices while maintaining economic efficiency. Moreover, replacing automobiles with drivers may enhance the attractiveness of public transportation and incentivize consumers to abandon personal car usage.

Furthermore, the production of power batteries leads to a significant discharge of pollutants [5], and there is now a need for a complete criterion for the recycling of batteries. Evaluating sustainable methodologies in the recycling process and addressing the numerous sustainability problems in the electric car field are of high importance for all stakeholders involved.

Notwithstanding these disadvantages, all-electric buses provide clear benefits. Electric buses are quieter during operation and have lower maintenance costs compared to the traditional fuel-powered buses. It makes them a more popular alternative choice [6]. With the increasing accessibility of environmentally-friendly power generation technologies, such as wind and solar, the actual carbon emissions resulting from the charging and operation of these buses are significantly reduced. The enhanced accessibility of charging stations has greatly enhanced the operational efficacy. If electric buses are successful in decreasing high carbon emissions over their lifespan, they can be an ideal alternative for urban transport [7].

Vehicles using electrical energy technologies have become a crucial storage foundation for the advancement of renewable energy [8]. The development of next-generation electric vehicles plays a major role in transition towards sustainable energy, especially for modern mega-storage technology. With the increasing usage of renewable energy, there is a prediction that the carbon emissions per km of electric vehicles will have a significant decrease. As a result, the growing prevalence on the roads is positioned to have a big influence on decreasing future carbon emissions, resulting in large economic benefits and a decreased carbon footprint.

Despite significant advancements in the electric buses research area, a straightforward and practical approach for calculating a vehicle’s energy usage in urban operating settings is lacking. This research employed an arithmetic method using a blind box model, enabling users to modify vehicle parameters, including length, weight, and frontal area, etc., to obtain an approximate estimation of energy consumption, which holds practical relevance.

2. Literature Review

Life cycle assessment (LCA) is a methodical process used to assess the environmental impacts and resource usage of products across their full life cycle. This includes activities like sourcing raw materials, manufacturing, usage, and waste management. The practical efficacy of LCA methodologies has been shown through significant transformations, leading to their widespread application in real-life scenarios. The Coca-Cola Company, Atlanta-USA, established the concept of LCA in 1969, having initially developed it as an environmental management tool in the United States [9].

The field of LCA has undergone substantial progress in the past three decades. In the 1970s, the analysis expanded from solely focusing on energy-related concerns to encompassing a broader scope of environmental implications. In subsequent decades, the approach was broadened to encompass the evaluation of the complete life cycle effects and expenses of items.

The majority of academics have employed LCA as a tool for conducting an environmental impact assessment (EIA). According to Tukker et al. [10], LCA is a more detailed version of the environmental assessment framework, whereas EIA is a process rather than a tool where LCA can be beneficial. Specifically, the consideration of process and abatement alternatives is particularly important in the assessment of strategy and project EIA. Also, LCA allows for a comprehensive assessment of the total environmental impacts associated with a product, process, or human activity [11].

After comprehending and analyzing the characteristics of LCA as a tool for analysis, Eriksson et al. chose to approach road transport from a life cycle viewpoint due to the significant volume of carbon emissions it produces each year [12]. Their article compiled comprehensive data on the environmental impacts resulting from various transportation activities, including fuel production, fuel burning during driving, vehicle maintenance, vehicle production, and disposal. The data were then converted into a format suitable for use in life cycle assessment.

Like everything else, the car industry started to slowly use the LCA evaluation method as time went on. Messagie et al. examined the methodology for evaluating the environmental impact of various vehicle technologies and proposed a range-based approach for conducting a life cycle assessment of vehicles [13]. They emphasized that solely considering tailpipe emissions is inadequate for a thorough evaluation of a vehicle’s environmental performance.

Ge Zheng, Zhi Junpeng et al. performed a study on the emissions of greenhouse gases (GHGs) from major energy sources and various stages of vehicle operation [14]. In addition, practical assessments were conducted on typical compact and subcompact electric cars, and vehicle utilization was determined through the implementation of real-time data gathering systems installed on the vehicles.

Electric vehicles exhibit superior sustainability in terms of both the environment and the economy when compared to alternative technologies. Syré et al. [15] conducted a comparative examination of battery and fuel cell systems, specifically focusing on electric cars, heavy-duty trucks, and city buses [16]. The findings suggested that both fuel cell and battery systems generate substantial emissions during the manufacturing stage.

Some of the major automakers, such as Audi, have also conducted LCA related research. The premium automaker uses LCA to find out where a car company stops and starts in terms of social, environmental, and economic duty, focusing on how important it is for a company to always think about the whole life cycle of a vehicle. Managing suppliers, protecting the environment, creating new technologies, like electric vehicles and synthetic fuels, and the difficulty of recycling car parts are some of the other points that need to be considered [15].

3. Research Methods

3.1. Life Cycle Assessment Methods

The concept of life cycle assessment emerged in the 1960s as a reaction to growing concerns about environmental deterioration and resource constraints. This chapter provides a concise overview of the history of LCA, featuring a specific emphasis on methodological advancements, practical applications, global alignment and standards efforts, as well as areas of knowledge distribution [17]. The early stages of LCA mostly originated from packaging research, including a specific focus on energy consumption and reduced pollution. This led to an inconsistent strategy in the development of methodologies in both the United States and the Nordic nations. These studies, mostly focusing on companies, were primarily used internally by companies and had limited communication with stakeholders. Following a period of relative calm in the 1970s, the scientific world experienced a surge in methodological advancement and global collaboration and coordination during the 1980s and 1990s. Universities played an increasingly significant role in driving methodological growth during this time. As the methodological issues became more solidified, the use of LCA grew to encompass a greater variety of products and systems [18].

The ISO, or International Organization for Standardization, released a comprehensive framework for carrying out life cycle evaluations from 1997 to 2000. This effort led to the establishment of the ISO 14040 [19], 14041 [20], 14042 [21], and 14043 [22] standards. The standards were later revised in 2006, consolidating the earlier standards into ISO 14040 and 14044 [23]. This standard use establishes principles and a framework for LCA, aiming to provide general requirements and guidelines for conducting LCA analyses.

3.1.1. Process-Based LCA

Process LCA, also known as process life cycle assessment, is a systematic evaluation of the resources and waste generated by each specific activity or process within a clearly defined system boundary. The evaluation is performed via the SETAC model to scrutinize the product system. It provides a concise summary of the results of each individual unit activity or process, including the inputs and outputs involved. Furthermore, it collects the input and output data for the complete product system across its entire life cycle. Process-based life cycle evaluation is a theoretical approach that employs a “bottom-up” technique. During the inventory analysis process, it is essential to meticulously examine and collect a significant amount of data related to actions that occurred earlier in the supply chain. Considering all preceding procedures, the process of inventory analysis usually requires more time and financial resources. Therefore, process-based LCA streamlines the analysis of product systems by including in the study’s system boundary the unit activities or processes that are considered important, based on factors such as weight, volume, etc., produced by the system, while ignoring those that are relatively unimportant.

3.1.2. Hybrid LCA

Hybrid LCA is an approach that integrates process-based and input-based life cycle assessment. It involves two types of hybrid LCA models: process-based hybrid LCA and input output-based hybrid LCA [24,25]. It combines the process data from process-based LCA with the input–output data from input–output-based methods. The approach considers the integrity, specificity, and comprehensiveness of the data to ensure precise and dependable results. Furthermore, the accuracy and trustworthiness of the results are ensured by considering the completeness, specificity, and comprehensiveness of the data.

Nevertheless, the lack of a comprehensive validation process model leaves the performance of hybrid LCA uncertain. Yang et al. [26], demonstrated through a counterexample that hybrid LCA may not always yield more precise outcomes compared to process-based LCA. This is due to the fact that the combination of diverse processes in the input–output (IO) model might potentially introduce additional inaccuracies. As a result, hybrid LCA is commonly used to study complex systems that do not emphasize the accuracy of the data.

3.1.3. Streamlined LCA

Streamlined LCA is a streamlined adaptation of the conventional LCA technique. Its purpose is to simplify LCA studies, making them less time-consuming and expensive, while still offering useful insights into environmental implications [27]. Recently, the car industry has faced substantial pressure to reduce its environmental impact. Regulators are endeavoring to steer the industry towards cleaner alternatives, while customers are modifying their purchasing patterns to prefer more sustainable items.

Manufacturers must increasingly view sustainability not only as a matter of compliance but more as an opportunity to obtain a competitive advantage by leveraging environmental issues. In response to this requirement, Arena and other researchers have devised a performance evaluation system to assist vehicle makers in assessing technological alternatives for sustainable mobility [28]. The system is founded on an examination of pertinent scientific and practitioner literature and suggests a collection of crucial sustainability metrics encompassing various stages of a vehicle’s life cycle, such as raw material acquisition, material production, product manufacturing, product utilization, end-of-life cycle, and transportation.

During the pre-conceptualization phase, a simple model can generate a first outcome expeditiously, thereby establishing the foundation for subsequent in-depth study.

3.1.4. Selected Method

This article focuses on evaluating the sustainability of hybrid buses compared to completely electric buses. The evaluation specifically looks at the use phase in the streamlined LCA method, with an emphasis on energy consumption as the indicator. This is a comprehensive assessment of a particular product (microsystem) that includes calculating the carbon emissions produced during its entire life cycle in a quantitative manner. However, it should be noted that the theoretical development of hybrid LCA is not yet fully comprehensive, and the existing input–output table has not been effectively integrated into the analysis of specific products.

In order to address the requirements of this study, the chosen article aims to simplify the traditional full life cycle model by utilizing traditional LCA. The main focus is on calculating energy consumption based on the WLTP Class2. The article also minimizes irrelevant variables by starting from a theoretical perspective of the previous period. This approach aims to enhance the reliability and accuracy of the analysis results. The next step is to direct our attention to the utilization stage of the buses.

3.2. Worldwide Harmonized Light Vehicles Test Procedure (WLTP)

To determine the energy consumption during vehicle operation and mitigate the impact of environmental factors on the analysis, we employed MATLAB R2021b software to conduct calculations. These calculations are based on the worldwide harmonized light vehicles test procedure test cycle.

The worldwide harmonized light vehicles test procedure (WLTP) is a standardized testing procedure employed to quantify the fuel consumption and emissions of passenger automobiles and light commercial vehicles inside controlled laboratory environments. It is based on the new driving cycles (WLTC—worldwide harmonized light-duty vehicles test cycles) to measure mean fuel consumption, CO₂ emissions, as well as emissions of pollutants.

In the process of developing the WLTP, the European Commission’s Joint Research Centre carried out testing on 21 petrol and diesel vehicles that complied with Euro 4–6 norms. The tests were conducted using both the European Driving Cycle (NEDC) and WLTP methodologies. The findings indicated a minimal disparity in the mean levels of CO₂ emissions between the new NEDC and WLTP assessments. Nevertheless, it was discovered that the CO₂ emissions recorded during the NEDC tests exceeded the legally sanctioned norms by an average of 9% [29]. This implies that within the WLTP, the discrepancy is anticipated to increase as the WLTP test program is fully executed. Most cars release cannabis under the acceptable limits, and overall emissions have decreased compared to the NEDC test. The shift from NEDC to WLTP has had negligible effects on nitrogen oxides (NOx) emissions in petrol vehicles and carbon monoxide (CO) emissions in diesel vehicles. However, the emissions of NOx from diesel vehicles and CO from low-power petrol vehicles significantly rose during the more demanding WLTP test. Indeed, in multiple cases, these emissions exceeded the specified thresholds [30].

The United Nations Economic Commission for Europe (UNECE) created the WLTP to replace outdated testing procedures like the NEDC. The WLTP was developed due to the inefficiency of prior testing cycles, such as the NEDC, in sufficiently capturing actual driving patterns and traffic situations. The NEDC, for instance, showed a decrease in acceleration and speeds, long periods of idling, and was unable to effectively describe recent automobile technology. The key features are as follows:

• The WLTP incorporates elevated rates of acceleration, more authentic velocities, and reduced durations of stops, so offering a more accurate portrayal of contemporary driving circumstances.
• The concept of driving phases encompasses four distinct segments characterized by varying average speeds: low, medium, high, and extra-high. Each component comprises a diverse range of driving stages, encompassing halts, acceleration, and deceleration.
• Diverse range of conditions: The cycle is specifically designed to encompass a broad spectrum of driving circumstances in order to assure its global applicability. This encompasses several environments, including urban, suburban, and motorway driving.

The WLTP is categorized into many classes according to vehicle parameters, namely the power-to-mass ratio, which is measured in watts per kilogram (W/kg). The power-to-mass ratio is determined by dividing the vehicle’s maximum net power by its curb weight. This categorization enables more customized testing that accurately reflects the performance attributes of many types of vehicles. It has four main classes:

• Class 1: For vehicles with extremely low power-to-mass ratios, which are less than or equal to 22 W/kg.
• Class 2: For vehicles with relatively low to moderate power-to-mass ratios, which are greater than 22 W/kg and up to 34 W/kg.
• Class 3a: For vehicles that have a significant power-to-mass ratio, ranging from moderate to high, which are greater than 34 W/kg. During the test the speed of the vehicle does not exceed 120 km/h.
• Class 3b: Has the same power-to-mass ratio as Class 3a, but the speed can exceed 120 km/h in the WLTP.

WLTP primarily focuses on passenger cars and light commercial vehicles weighing less than 3.5 tones. It incorporates more intricate start–stop circumstances and is divided into four distinct stages:

• Low—emulates urban driving conditions characterized by slow velocities and frequent instances of commencing and ceasing movement.
• Medium—emulates the experience of driving in a suburban area, with a moderate speed and a reduced number of stops.
• High—emulates the experience of driving on a highway, with fast speeds and uninterrupted driving.
• Extra high—emulates the experience of driving at extremely high speeds, specifically designed for high-performance vehicles.

This simulation faithfully recreates a bus route of medium to long distance, covering motorways. Although this standard is not specifically designed for commercial cars, there is currently a dearth of test methods for commercial vehicles that are comparable to the WLTP. The difference between the two test standards is shown in

Table 1. Comparison between WLTP and NEDC.

	WLTP	NEDC
Driving Conditions, this refers to the various factors that affect vehicle performance and emissions, such as speed, traffic congestion, road incline, weather, and driving habits.	Realistic speeds, increased acceleration, minimized idling.	Lower acceleration, longer idle times, less realistic speeds.
CO2 Emissions, a greenhouse gas produced primarily from burning fossil fuels in vehicle engines.	More accurate measurement—the disparity grows once WLTP is fully deployed.	When compared to legal norms, the estimate was 9% higher.
NOx Emissions, a group of gases (mainly NO and NO₂) produced during combustion, especially at high temperature.	The effect on petrol automobiles is negligible, but diesel vehicles see a large increase.	Lower for diesel vehicles.
CO Emissions, A colorless, odorless, and toxic gas produced by incomplete combustion of fuel.	Diesel vehicles are unaffected, but low-power gasoline vehicles see a large rise.	Lower for low-power petrol vehicles.

. Therefore, it is desirable to experiment with it on a theoretical calculation level.

Let us consider an actual case of an electric bus that operates solely on electricity and has a weight of 17 tons, while being 12 m in length. The maximum power output of this bus is 375 kW. By making a calculation of the vehicle’s power-to-weight ratio, we obtain a value of 22.06 W/kg. The weight and power of the vehicle can be modified if necessary. Regardless of the circumstances, based on the above information, it is recommended to use the WLTP Class 2 standard.

3.3. Parameter Definition and Calculation

First, we define the electric bus parameters as below.

• Vehicle mass: 17,000 kg
• Vehicle front area: 5.1 m²
• Rolling resistance: miu = 0.006
• Slope of the road: alpha = 0
• Gravity value: g = 9.8 m/s²
• Air density: phi = 1.29 kg/m³
• Atmospheric drag coefficient: Cd = 0.35
• Differential efficiency: EDiff = 0.95
• Differential ratio: Gear Ratio = 23
• Wheel radius: R = 0.957/2 m, 275/70 R22.5
• Transmission ratio: GR = 1
• Transmission efficiency: ETrans = 0.96
• Battery energy: EnergyMax = 604 × 232.5 × 12 × 3600 J
• Battery parameter: Voltage = 151 v, content = 232.5 × 12 Ah, l = 800 A, unit = 4, 250 v–400 v, battery voltage = 360 v
• Initial state of charge at the beginning: EnergyEM(1) = 0.8 × EnergyMax

Due to variations in motor efficiency, it is not possible to establish a fixed value for this number. The efficiency of the motor is subject to variations based on factors such as temperature, speed, and other operational variables. An electric motor efficiency map is a graphical representation that depicts the efficiency of an electric motor in converting electrical energy into mechanical power across different operating situations. It delineates efficiency as a function of motor speed (RPM) and torque (Nm). These test results indicate the concept referred to about a high-power motor. The results are shown in

Table 2. Electric motor efficiency data.

Electric Motor Efficiency
Speed (RPM)		2000	4000	6000	8000	10,000	12,000
Torque (Nm)	0	0.55	0.56	0.57	0.58	0.59	0.6
	50	0.9	0.947	0.95	0.95	0.952	0.945
	100	0.91	0.94	0.948	0.957	0.952	0.94
	150	0.9	0.935	0.947	0.95	0.93	0.91
	200	0.88	0.925	0.942	0.945	0.9	0.89
	250	0.85	0.92	0.935	0.93	0.91	0.89
	300	0.82	0.91	0.925	0.9	0.88	0.82
	350	0.85	0.89	0.915	0.9	0.85	0.78
	100	0.75	0.88	0.9	0.85	0.8	0.75

The following are the WLTP test process data.

and

Table 3. WLTP Class 2 test process data [31].

	Duration	Stop Duration	Distance	P_stop	V_max	V_ave Without Stops	V_ave with Stops	A_min	A_max
Unit	s	s	m		km/h	km/h	km/h	m/s2	m/s2
Low	589	155	3132	26.3%	51.4	26.0	19.1	−1.07	0.92
Medium	433	48	4712	11.1%	74.7	44.1	39.2	−0.99	0.96
High	455	30	6820	6.6%	85.2	57.8	54.0	−1.11	0.85
	1477	233	14,664

below.

The figures clearly demonstrate that the WLTP driving cycle is split into four sections, each characterized by distinct average speeds: low, medium, high, and extremely high. Each component consists of a diverse range of driving stages, halts, periods of acceleration, and periods of braking. Compared to the previous version, it is more closely aligned with the current driving circumstances.

Once we import the driving cycle data, we are able to calculate the forces. The force analysis of the vehicle conducted here is primarily theoretical, disregarding the intricate and variable cycle loads encountered in real-world scenarios. It is better suited for stable working settings, such as those commonly found in a laboratory setting, while it still maintains a certain amount of relevance.

• Gravity force: $F_g\left(i\right)=m\times g\times \sin \left(alpha\right)$
• Drag force: $F_d=1/2\times A\times phi\times cd\times {V\left(i\right)}^2$
• Acceleration force: $F_a=m\times a\left(i\right)$
• Resistance force: $F_r=m\times g\times miu$

By summing the above forces on the vehicle, we can obtain the sum of forces on the vehicle under ideal road conditions. Figure 1 shows the electric motor power calculation process. With analyzing the rotational speed of the vehicle’s wheels, we can determine the power and torque of the differential. From there, we can infer and compute the power and torque of the vehicle’s gearbox. Finally, we can calculate the speed, torque, and power characteristics of the electric motor. The calculation results are shown below.

Power/Torque EM: Power/Torque of electric motor.

Based on the calculation findings, which shows in Figure 2, the vehicle’s maximum power during forward movement in the WLTP test was 218.868 kW, while during deceleration it reached 299.89 kW. These power levels also satisfy the requirements for the vehicle’s actual driving situations. The electrical energy usage throughout the 14.664 km test was 21.28 kWh, resulting in an average consumption of 1.451 kWh per km. This level of energy use is acceptable [32]. The algorithm’s computations and subsequent comparisons with actual vehicle data meet the criteria of real-world application scenarios and align well with the data given by electric bus manufacturers. The results are also in proximity to those computed by certain established power consumption prediction methods [33].

Now we define the hybrid bus parameters:

• Vehicle mass: 16,000 kg
• Differential ratio: Gear Ratio = 4
• Transmission ratio: GR = 18
• First gear: Gear = 1
• Engine speed min: nE_min = 800 rpm
• Engine speed max: nE_max = 1800 rpm
• Battery energy: EnergyMax = 151 × 232.5 × 12 × 3600 J
• Battery parameter: Voltage = 151 v, content = 232.5 × 12 Ah, l = 800 A, unit = 1, 250 v–400 v, battery voltage = 360 v

The rest of the data remains consistent with electric buses. Aside from the standard force calculations, it is important to include the vehicle’s lateral movements when driving and the precise timing of the engine’s intervention in hybrid mode. The former establishes the operational boundaries by constraining the lowest and highest engine speeds, whilst the latter use SOC (state of charge) to ascertain the engine’s activation. The gear change logic and hybrid powertrain logic are shown in Figure 3 and Figure 4 below.

Engine fuel consumption is determined by the BSFC (brake specific fuel consumption) curve for diesel engines. A BSFC map is a graphical depiction of an engine’s fuel efficiency across various operating circumstances. The data which uses in this code was shown in

Table 4. BSFC map data.

BSFC g/kW⋅h
Speed (RPM)		800	1000	1200	1400	1600	1800
Torque (Nm)	0	300	305	308	310	311	310
	100	250	256	264	275	288	296
	200	222	228	232	236	242	247
	400	209	204	202	206	214	221
	600	192	192	194	196	199	205
	800	204	191	186	187	192	200
	1000	200	190	186	188	190	198
	1200	201	191	184	186	189	196
	1400	254	234	240	237	242	243
	1600		192	182	186	189	195
	1800			184	185	191	194

. The fuel consumption rate (in grams of gasoline per kilowatt-hour, g/kWh) is depicted as a function of engine speed (RPM) and load (torque or brake mean effective pressure, BMEP). The subsequent Table 4 presents these statistics.

Based on the calculations, which shows in Figure 5, the vehicle’s maximum power during the WLTP test was 207.156 kW while accelerating and 283.403 kW while decelerating. These power levels also satisfy the demands of the vehicle’s real-world driving conditions. The fuel usage throughout the 14.664 km test was 3.7109 L, resulting in an average of 25.3 L per 100 km. This level of energy use is acceptable. The current average fuel efficiency of hybrid buses ranges from 25 to 40 L [34] per 100 km. The aforementioned simulations are essentially consistent with the actual test outcomes.

After performing thorough empirical validation and lengthy numerical computations, it is evident that the underlying logic and overall structure described above can be modified to meet relatively straightforward tasks. However, the behavior of real vehicles can sometimes be more complex than these basic movements, necessitating the use of advanced equations and precise evaluations of pressures. Moreover, while the WLTP method is widely acknowledged as a benchmark for assessing energy consumption in the automobile sector, ongoing deliberation and scrutiny persist on its applicability to testing larger vehicles. Hence, it is imperative that forthcoming research endeavors prioritize the pursuit of further validation to determine conclusively its appropriateness for such objectives.

4. Results Analysis

4.1. Energy Consumption Analysis

Given the current emphasis on the energy usage of various cars, the earlier calculations enable us to derive results based on the WLTP test, which specifically measures energy consumption during the use phase; it is called “tank to the wheel”. Once a product has been manufactured, it undergoes the “well to tank” phase, which involves logistics, storage, and energy supply processes before it can be used. The outcomes differ based on the energy source.

Rokicki et al. conducted a study on the variations in energy usage within the transportation sector among EU countries. They employed hierarchical data analysis as one of the techniques for analyzing multiple variables. The study analyzed data from the years 2004 to 2018 and found that EU countries had shown a consistent trend of decreasing energy usage, both overall and specifically in the transportation sector [35].

The European continent’s limited history in oil production and dependence on energy imports make its supply chain typically susceptible to disruption. The situation in eastern Ukraine has created new challenges for the transportation of gas and oil pipelines in the region [36]. This problem is particularly acute in specific Central and Eastern European countries. As a result, there have been few research endeavors focused on studying the fuel production phase.

Due to several drawbacks, a number of individuals in Europe have directed their attention towards conducting research on biofuels. Biodiesel can be produced from both fresh and used vegetable oils and animal fats, all of which are non-toxic, biodegradable, and renewable resources. Previously, vegetable oil fuels were not deemed acceptable due to their higher cost compared to petroleum-based fuels. Recently, biodiesel has gained appeal as a result of the environmental advantages it provides [37]. Given the increasing expense of oil and the ambiguity around its accessibility, there is a renewed emphasis on utilizing vegetable oil as a fuel for diesel engines. Biodiesel is the primary biofuel used in Europe [38].

In North America, things are different. Rahman et al. endeavored to measure the complete life cycle greenhouse gas (GHG) emissions of transportation fuels derived from five conventional North American crudes in North America [39]. They achieved this by utilizing an LCA model known as FUNNEL-GHG-CCO (Fundamental Engineering Principles Modelling Based on Conventional Crude Oil Greenhouse Gas Estimates). The model calculates greenhouse gas emissions at every stage of the life cycle, starting from the extraction of crude oil and ending with the combustion of the fuel in car engines.

Considering the previous calculations, which include energy consumption and cost [40], it is evident that pure electric buses are the most advantageous option for bus transit. This is due to the widespread availability of electric energy as a cost-effective secondary energy source on a global scale.

4.2. Electricity vs. Fossil Fuels

Electricity, now the most extensively consumed form of renewable energy worldwide, has not only expedited the adoption of renewable energy as a replacement for fossil fuels in electricity generation due to its significant cost reduction, but has also started to supplant fossil fuels in other sectors [41]. At the moment, the cost of renewable power per unit of energy is lower than the value of oil, and it is approximately identical to the cost of fossil methane [42]. However, it is still more costly than coal. Also, electricity frequently provides alternative advantages, such as more affordable transportation, enhanced regulation, increased energy efficiency in the ultimate provision of energy services, and in reduced local environmental expenses. Carpejani and other scholars analyzed various sustainable energy sources, including solar, wind, hydroelectric, thermoelectric, tidal, biogas, geothermal, and hydrogen energy [43]. They highlighted the advantages of using these sources, such as their positive impact on environmental protection. However, they also acknowledged the main obstacle to their widespread adoption, which is the significant upfront investment required. Since there is currently no framework available for comparing various sources of energy, this new study is anticipated to act as an introductory guide for researchers and experts in the sector. As a result of the intricate nature of our socio-economic systems, each unit of alternative energy utilized for non-fossil fuel energy in the last 50 years has not completely substituted one unit of fossil fuel energy, but rather less than a quarter [44].

Given that the author resides and operates in Hungary, the ensuing discourse will revolve around this geographical location. Hungary’s electrical generation mix consists mostly of nuclear, natural gas, coal, and renewable energy sources. The following data are from Our World in Data [45] and Hungarian Central Statistical Office (KSH) [46]. Figure 6 shows the composition of electricity in Hungary.

• Hungary ranks third in terms of the proportion of nuclear power among member countries of the International Energy Agency (IEA), following France and Slovakia. The extension of the service life of the current units at the Paks nuclear power plant by 20 years (2032–2037) allows nuclear power to continue playing a significant role in the energy mix. There is a possibility that the scheduled building of two further units at the Paks facility, which is being funded by Russian investment, may experience substantial delays.
• Approximately 26.5% of the electrical mix is attributed to natural gas, making it a substantial source. The clear evidence of Hungary’s substantial reliance on fossil fuels to fulfil a significant amount of its energy needs is apparent.
• Coal remains a prominent source of energy, contributing approximately 15.5% to the overall energy generation. However, there are plans to progressively phase out the effective use of coal by 2030.
• Alternative energy sources: Renewable energy sources, such as biomass, wind, and solar power, make up around 13.4% of the total energy contribution. Currently, biomass is the predominant source of renewable energy, with wind and solar power in close pursuit. Both wind and solar electricity have been consistently increasing in terms of their capacity and output.
• Additional sources: A tiny fraction is derived from alternative sources, such as hydroelectric electricity, which remains relatively insignificant in Hungary due to its geographical and climatic characteristics that are not conducive to extensive hydropower generation.

It is well acknowledged that the addition of non-fossil fuels in electricity generation leads to a drop in CO₂ emissions. However, the extent of how it reduces subsequent emissions remains uncertain. Liddle et al. conducted an analysis on a large number of samples and discovered that the overall elastic of replacement for non-fossil fuel consumption per person is approximately −0.38 [47]. However, when it comes to the number of non-fossil fuels applied for generating electricity, these long-term elastics of substitution are −0.82. Therefore, a mere 1 percent rise in the proportion of non-fossil fuels utilized for generating electricity results in a reduction of around 0.82 percent in per capita CO₂ emissions from electric power generation. Only when the entire electrical infrastructure is sufficiently clean, can we truly claim that electrically driven vehicles have zero emissions throughout their operation.

The current global energy demand exceeds 12 billion tons of oil equivalence per year, leading to the release of 39.5 gigatons of carbon dioxide (Gt-CO₂). As energy demand is projected to rise to 24–25 gigatons, annual CO₂ emissions are expected to reach 75 gigatons [48]. Although oil, gas, and coal are expected to persist for many years, it is imperative to undergo an energy transition towards fuels with low carbon intensity in order to effectively address the widespread issue of climate change. The transport industry in Hungary has a notable oil consumption, which constitutes a considerable proportion of the country’s total oil usage. In 2022, the total oil consumption in Hungary amounted to 7.8 million tons, with the transport sector accounting for 59% of this quantity [49]. This underscores the industry’s significant dependence on oil-based products. In the past ten years, Hungary has seen a significant increase in oil consumption, specifically in the transportation industry. From 2013 to 2019, the country experienced a 5.5% average yearly rise in oil consumption. Nevertheless, this expansion has reached a point of stability in recent years, sustaining a consistent level up to 2022 [50].

Owing to the finite supplies of fossil fuels and their detrimental effects on the environment, numerous nations are currently shifting towards renewable energy sources in order to guarantee energy security and promote sustainable development. Biodiesel is a sustainable and environmentally friendly biofuel that can be broken down naturally. It shares similar characteristics with fossil diesel fuel. Based on recent data, it can be seen that Hungary is progressively incorporating biofuels, such as ethanol and biodiesel, into its energy blend in order to diminish greenhouse gas emissions and enhance energy security. The nation’s renewable energy program prioritizes the utilization of biofuels and is supported by rules that promote the mixing of biofuels with traditional fuels. The International Energy Agency predicts that there will be an almost 30% rise [51] in worldwide demand for biofuels between 2023 and 2028. This increase will be driven by both biodiesel and ethanol. Hungary’s strategic energy goals align with the global trend of increasing the utilization of biofuels as a key component of their overall renewable energy strategy.

In Hungary, the proportion of ethanol in fuel is approximately 8.7% as of 2023, which aligns with the overall aim set by the European Union. The proportion of biodiesel in diesel fuel is approximately 10% [52]. These statistics are a component of a continuous endeavor to enhance the utilization of biofuels with the aim of diminishing greenhouse gas emissions and lessening reliance on fossil fuels. The biofuels business has received support from EU laws and subsidies designed to encourage renewable energy, which has partially mitigated the production expenses. Nevertheless, the economic feasibility of biofuels continues to face obstacles due to the instability of feedstock costs and the rivalry with fossil fuels. For now, the production cost of biodiesel that may be used as vehicle fuel is approximately EUR 0.7–1.0 per liter [53]. This cost does not include expenses related to storage, delivery, taxes, and fees. Conversely, electricity has a conclusive retail cost of approximately EUR 0.2 per kWh [54], resulting in a notable cost benefit when it comes to practical utilization and functioning. Thus, in the immediate future, electricity remains the favored option over biofuels in order to meet the emission reduction goals with the usage of automobiles.

5. Conclusions

The objective of public transport is to offer a comfortable and economical mode of transportation for individuals who lack their own vehicles or opt not to possess one. The advocacy for electric and hybrid buses, as embodiments of low-carbon transportation, is crucial for mitigating carbon emissions in urban areas. The attributes of public transportation networks differ significantly across cities and regions, shaped by factors including population density, infrastructure quality, and governmental regulations. The primary attributes of this product are cost-effectiveness, environmental sustainability, and inclusive design for individuals of all ages. The decarbonization of private automobiles alone is inadequate to realize the complete efficacy of urban space management solutions. This paper analyzed the energy performance of electric and hybrid buses during the operational phase using LCA methodology, simulated in MATLAB with a blind box model. The WLTP Class 2 regulations were employed to evaluate the energy performance of these buses in conjunction with the composition of the Hungarian electricity system, highlighting the sustainability benefits of electric buses.

The energy consumption of two kinds of buses—hybrid diesel buses and pure electric buses—was simulated in the LCA-based practical phase study. According to the calculations, in terms of energy usage, pure electric buses considerably outperform hybrid diesel buses. Under the same test settings and experiencing 1800 s of challenging working conditions, specific results indicate that the average energy consumption of pure electric buses is 1.451 kWh/km, whereas the average energy consumption of hybrid buses is 25.3 L/100 km (approximately 2.53 L/km). Electric buses consume much less energy than hybrid buses, which also translates into reduced running costs.

While a lot of Hungary’s electricity mix comes from fossil sources, electric buses nevertheless have far fewer carbon emissions than hybrid buses. As the proportion of renewable energy rises, the advantages to the surroundings of electric buses will become more important. The aims for renewable energy development in Hungary offer great help for the introduction of electric buses. The percentage of 13.9% of Hungary’s total energy consumption came from renewable energy sources in 2019, which is somewhat more than the 13% target set for 2020. By 2030 Hungary wants to raise this share to 21% and maybe even to 23–25% [55]. The major sources of renewable energy are solar and biomass; wind and geothermal energy have promise for more growth. Nevertheless, at about 330 megawatts, the present installed capacity of wind energy is somewhat modest.

Although fossil fuels continue to dominate Hungary’s electricity mix, electric buses offer considerable environmental benefits. As the proportion of renewable energy sources increases and the charging infrastructure improves, the sustainability benefits will grow. Future studies can broaden the scope of LCA to include more locations and scenarios with varying power mixes, providing more comprehensive decision support. Also, through collaborative development with intelligent transportation systems and renewable energy, the promotion of electric buses will give a significant impetus for the green transformation of urban transport.