Minibus taxi public transport is a seemingly chaotic phenomenon in the developing cities of the Global South with unique mobility and operational characteristics. Eventually this wide-spread fleet of minibus taxis will have to transition to electric vehicles. This paper examines the impact of this inevitable evolution on a city-wide scale in Kampala, Uganda. We present a generic simulation environment to assess the grid impact and charging opportunities, given the unique paratransit mobility patterns. We used floating car data to assess the energy requirements of electric minibus taxis, which will have a knock-on effect on the region’s already fragile electrical grid. We used spatio-temporal and solar photovoltaic analyses to assess the informal and formal stops that would be needed for the taxis to recharge from solar PV in the region’s abundant sunshine. The results showed that the median energy demand across all simulated days of the fleet of taxis was 220 kWh /d. This ranged to a maximum of 491 kWh /d, with a median charging potential (stationary time) across taxis of 8 h /d to 12 h /d. The median potential for charging from solar PV ranged from 0.24 kWh/m2 to 0.52 kWh/m2 per day, across the taxis. Our simulator and results will allow traffic planners and grid operators to assess and plan for looming electric vehicle roll-outs to the most-used mode of transport in Africa. 

https://engrxiv.org/preprint/download/1855/3773

Walking on sunshine: Pairing electric vehicles with solar energy for sustainable informal public transport in Uganda

Traffic congestion, dominated by private mobility, reveals not only negative impacts on road safety and the environment, but also on community cohesion. With the global COVID-19/SARS-CoV-2COVID-19 (COVID-19) epidemic, there is an urgent need for social isolation and the use of individual private transport as per the approved health guidelines. Urban transport, especially public transportation (PT), is among the primary sectors affected due to the COVID-19 pandemic. Thus, novel alternatives for competitive PT services still have to be provided to remain meeting the socio-economic and ecological PT challenges. In this respect, sharing PT vehicles carrying passengers (shared freight-PT) could exploit a significant residual capacity as absorptive capacity is actually reduced. However, such use is based on a large-scale mutualization. The idea of integrating freight in passenger transit networks could be efficient within a Physical Internet (PI or π) framework for improving system monitoring, operational performance and, user comfort. This paper explores the major trends in the theory and practice of shared transport systems, in terms of passengers and freight, and suggests a PI conceptual framework to check if we could promote such logistics. In exploring the PI approach, a number of proposals appear providing answers and advance researches towards shared freight-PT.

Shared public transport within a physical internet framework: Reviews, conceptualization and expected challenges under COVID-19 pandemic

Ray of hope for sub-Saharan Africa's paratransit: Solar charging of urban electric minibus taxis in South Africa

Stochastic analysis of future scenarios for battery electric vehicle deployment and the upgrade of the electricity generation system in Spain

This study reports the likely real-world effects of fleet replacement with electric vehicles (EVs) and higher efficiency EURO 6 vehicles on the exhaustive emissions of NOx, PM, and CO2 in the seven boroughs of the West Midlands (WM) region, UK. National fleet composition data, local EURO distributions, and traffic compositions were used to project vehicle fleet compositions for different roads in each borough. A large dataset of real-world emission factors including over 90,000 remote-sensing measurements, obtained from remote sensing campaigns in five UK cities, was used to parameterize the emission profiles of the studied scenarios. Results show that adoption of the fleet electrification approach would have the highest emission reduction potential on urban roads in WM boroughs. It would result in maximum reductions ranging from 35.0 to 37.9%, 44.3 to 48.3%, and 46.9 to 50.3% for NOx, PM, and CO2, respectively. In comparison, the EURO 6 replacement fleet scenario would lead to reductions ranging from 10.0 to 10.4%, 4.0 to 4.2%, and 6.0 to 6.4% for NOx, PM, and CO2, respectively. The studied mitigation scenarios have higher efficacies on motorways compared to rural and urban roads because of the differences in traffic fleet composition. The findings presented will help policymakers choose climate and air quality mitigation strategies.

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Real-World Contribution of Electrification and Replacement Scenarios to the Fleet Emissions in West Midland Boroughs, UK

Optimizing electricity consumption to minimize wastage and reduce cost is a major challenge in many industries. This is because, in many cases, the effect of the independent variables contributing to the total electricity consumption and cost are latent. The purpose of this study is to apply numerical techniques to identify and optimize these independent variables in order to improve sustainable energy management in industries to minimize wastage. Regression analysis was first applied to identify and decouple the independent variables to determine their individual effects on electricity consumption and cost. A cost function called the Mean Square Error (MSE) was then used to optimize these independent variables using gradient descent algorithm (GDA). In a case study, the developed approach that combines time series regression analysis with gradient descent optimization was used to analyze the electricity consumption data of an oil distribution company for the period 2015 to 2018. The results showed potential electricity savings of 124,684 kWh and cost savings of US$ 25,375 annually, when the facility is operated at optimum parameters of 0.95 power factor, 260 kVA maximum demand and 25,000 kWh active electricity consumption. The novelty of this study is that a procedure that combines time series regression analysis (RA) and gradient descent algorithm (GDA) has been developed and applied to decouple and optimize the independent variables that affect electricity consumption in an industry. 

Optimization of industrial energy consumption for sustainability using time-series regression and gradient descent algorithm based on historical electricity consumption data

Urban transport contributes more than a quarter of the global greenhouse gas emissionns that drive climate change; it also produces significant air pollution emissions. Furthermore, vehicle collisions kill and seriously injure 1.35 and 60 million people worldwide, respectively, each year. This paper reviews how vehicle telematics can contribute towards safer, cleaner and more sustainable urban transport. Collection methods are reviewed with a focus on technical challenges, including data processing, storage and privacy concerns. We review how vehicle telematics can be used to estimate transport variables, such as traffic flow speed, driving characteristics, fuel consumption and exhaustive and non-exhaustive emissions. The roles of telematics in the development of intelligent transportation systems (ITSs), optimised routing services, safer road networks and fairer insurance premia estimation are highlighted. Finally, we outline the potential for telematics to facilitate new-to-market urban mobility technologies, signalised intersections, vehicle-to-vehicle (V2V) communication networks and other internet-of-things (IoT) and internet-of-vehicles (IoV) technologies.

/pdf/vehicle-telematics-for-safer-cleaner-and-more-sustainable-3qj3mxd0.pdf

Vehicle Telematics for Safer, Cleaner and More Sustainable Urban Transport: A Review

/pdf/real-world-contribution-of-electrification-and-replacement-580yo2u4s6.pdf

Louisa K. Osei

Papers

Real-World Contribution of Electrification and Replacement Scenarios to the Fleet Emissions in West Midland Boroughs, UK

Optimization of industrial energy consumption for sustainability using time-series regression and gradient descent algorithm based on historical electricity consumption data

Vehicle Telematics for Safer, Cleaner and More Sustainable Urban Transport: A Review

Real-World Contribution of Electrification and Replacement Scenarios to the Fleet Emissions in West Midland Boroughs, UK