Electric Public Bus Research Articles

CARBON EMISSION INTENSITY FOR MELAKA GREEN TECHNOLOGY CITY STATE

The study analyzes the carbon emission absolute number and intensity for Melaka state as a response to the Malaysia voluntary reduction target of up to 40 percent in terms of emissions intensity of gross domestic product, GDP by the year 2030 compared to 2005 levels. It is manifested in the vision of Melaka Green Technology city state by 2020. The Global Protocol for Community-Scale Greenhouse Gas Emissions, GPC method deploys to calculate greenhouse gas, GHGs emission resulted from the various development activity in Melaka. This method classified GHG emissions into four (4) mains sectors: stationary energy, transportation, waste, and agriculture, forestry, and other land use (AFOLU) by using secondary data from related government agencies at the state level. The computation by BASIC+ reporting level resulted from an output of GHGs emission translated into carbon emission. Steady increase of GHG emissions was captured from 8,859,802 tCO2e (2013) to 8,911,173 tCO2e (2017). Further, carbon emission intensity calculates by gathering the carbon emission absolute number to Melaka’s population. The emission per-capita increase from 6.19 tCO2e (2013) to 6.88 tCO2e (2017), indicates each person contributes to the increment of GHGs emissions for Melaka state. However, the decrease of emission intensity records from 0.189 tCO2e (2013) to 0.176 tCO2e (2017) compared to an increase in population growth. The study concludes certain influences of the aggressive green technology initiative effect, such as renewable energy, LED street lighting, solar valley, smart metering in the building, electric public bus, no plastic bag, waste recycling to the overall carbon emission intensity of Melaka Green technology City State.

Strategic Planning of Charging Stations for Electric Public Transportation Bus Systems: a Case Study

Fuel and natural gas are the main factors that drive many systems in many countries, but they have decreased because of the increased demand. However, the use of diesel fuel in public transport is one of the main reasons for the deterioration of air quality in the city. This article studies the strategic planning of charging stations for electric public transportation bus systems. Furthermore, it analyzes the investment costs of the service of electric buses compared with diesel buses by using routes in the city of Nakhon Ratchasima as a case study. The energy consumption of electric buses will also be analyzed in this article. The analysis shows that the electric bus has an energy consumption for traveling 1.169 kWh/km, and ten buses are services in one day. The electric bus charging strategy with the Plug-in charging system is the most suitable one, compared to the diesel bus system and the other charging strategies, since it has lower total investment cost of 11.37 million USD, and the battery investment is the highest one. The appropriate charging strategy depends on the route of the case study as well. If the distance is longer, the calculation of the charging station's investment, the number of buses, and the batteries may increase accordingly.

Estimation of the energy demand of electric buses based on real-world data for large-scale public transport networks

An increasing number of cities are transitioning from fossil fuel-powered buses for public transport to battery electric buses. Evaluating the energy demand of buses has become an important prerequisite for the planning and deployment of large electric bus fleets and the required charging infrastructure. A number of state-of-the-art approaches to determining the energy requirements of electric buses use individual specific energy demand values or rely on standard driving cycles, though these do not consider local bus route characteristics. Others require high-resolution measurements of the vehicles’ driving profiles, which is impractical for large bus fleets. This paper presents a longitudinal dynamics model to calculate the energy demand for electric buses. The model is designed to be easily applied to large bus networks using real data sources that are commonly available to bus transit operators. This data can be derived from low-resolution data collected from day-to-day operations, where only the arrival and departure time of the buses at each bus stop are available. This approach offers a practical alternative to state-of-the-art methods and requires no high-resolution velocity profiles, which are difficult to obtain, while still taking into account the details of the operational characteristics of the transportation network under consideration. The application of the model is demonstrated in a case study to electrify the complete public bus network in Singapore. The results showed that the heterogeneity of driving conditions observed in a large network leads to a high variance in energy requirements between different bus lines and at different times of day. This confirms the need to take the characteristics of each individual bus route into account. In the case-study, a fully electric public bus fleet would require about 1.4 GWh per day for revenue service, which is about one per cent of Singapore’s daily electricity demand. Another finding is that 50% of the bus lines require less than 40 kWh per terminus-to-terminus journey, which indicates a good potential for fast opportunity charging during layover time. The results of the model should serve as the basis for further studies into battery sizes, charging strategies and charging infrastructure requirements.

Could urban electric public bus really reduce the GHG emissions: A case study in Macau?

The urban bus fleet has been significantly expanded to satisfy an increasing demand for transit in Macau, highlighting the need for green transport. Electric public buses (EPBs) have been considered an effective strategy to reduce greenhouse gas (GHG) emissions by substituting them for diesel buses. However, the efficiency of EPBs to reduce GHG emissions varies significantly, due to local road conditions and transit operating characteristics. On the basis of the real-world tested data, this study performed a comparative life cycle assessment (LCA) between traditional diesel public buses (TDPBs) and EPBs to evaluate the actual GHG emissions and their reduction. The results show that the mean GHG emissions per 100 km of diesel light duty buses, medium duty buses and heavy duty buses were approximately 47.18, 101.97, and 127.99 kg CO2 eq, respectively. The EPBs supported by current electricity mixes exceed the emissions of corresponding TDPBs when considering the charging loss and electricity distribution loss. EPBs, therefore, would hardly reduce GHG emissions under the current situations. Due to the rapid growth in the number of urban buses, total GHG emissions from TDPBs in 2001–2015 experienced a rapid upward trend, increasing from 36.55 to 48.86 thousand tons CO2 eq. Scenario analysis for future EPBs substitution implies that, if choosing the best charging efficiency and electricity distribution loss, EPBs have the potential to significantly mitigate the GHG emissions from public buses, especially under the clean electricity mixes (like natural gases fired electricity and solar energy).

Accommodating preference heterogeneity in commuting mode choice: an empirical investigation in Shaoxing, China

ABSTRACTA latent class model is developed to accommodate preference heterogeneity across commuters with respect to their mode choice between electric bike, private car, and public bus within the context of China. A three-segment solution – ‘electric bike individuals’, ‘private car addicts’, and ‘public bus enthusiasts’ – is identified, each characterized by heterogeneous preferences regarding specific mode attributes and unique socio-demographic profile. The choice model confirms the determinative effects of perceived alternative attributes on commuting mode choice, while the traditionally used objective attributes – travel time and cost – are found to have relatively small influences. The membership model provides solid explanations for these segment-specific preferences. This study provides a better understanding of the nature of mode choice behavior, which can be useful for strategies tailored to a specific segment in order to promote the use of sustainable transport modes.

Implementation of Energy Storage System with Fleet Management on Electric Shuttle Buses

Electric public bus scheduling problem is studied for the service in Chulalongkorn university campus. This paper presents an integrated bus scheduling simulation combined with options of energy storage system with the target to minimize the wait time. The bus system is simulated by Arena software for the bus scheduling. The solution dictates the change of the bus schedule; the resulting change of wait time is then observed. Lead-acid equipped with supercapacitor and lithium-ion batteries were compared in this study to exhibit the improved performance. The supercapacitor hybrid and lithium-ion battery provides an improvement of 14% and 45.7% in discharge energy, respectively. The supercapacitor hybrid was shown to reduce battery stress as well as improved driving dynamics. The optimized lead-acid case can reduce the waiting time significantly and at the similar level to the supercapacitor hybrid. With much higher cost, the lithium-ion battery reduce the waiting time the most by 25% due to its superior energy efficiency as well as shorter charging period.

A Sensitivity Analysis of Total Cost of Ownership for Electric Public Bus Transport Systems in Swedish Medium Sized Cities

To reach Swedish national climate change reduction targets, organizations collaborate for a sustainable development to improve energy efficiency, reducing pollution and noise in public bus transport. This follow-up study continues to strengthen the previous study by deepen the economic comparisons of two electric buses with different driving range and different type of chargers. The study aims to emphasize on sensitivity analysis for the total cost of ownership (TCO) to reduce uncertainty by identifying which factors of interest that most likely cause the estimated cost values for the electric bus. The result shows that the percentage change of line distance (km/year), operational years, and investment cost would be the most influential and significant factors on TCO.

Application study on a control strategy for a hybrid electric public bus

This paper first describes the control strategy used in a hybrid electric public bus and then proposes a torque-balancing control strategy. Simulations were performed using the designed control strategies, and the results were analyzed under different conditions. The torque-balancing control strategy was improved on the basis of the efficiency-first ideas of the hybrid system. Finally, experiments were performed to verify that the efficiency-first and torque-balancing control strategy (EFCS) is both feasible and reliable. The simulation results showed that, compared with a conventional public bus, the hybrid electric bus could save approximately 27.3 percent on fuel consumption using the EFCS control strategy in a public bus in China, while under the Wuhan urban driving cycle.