Methodology for adjusting the standard frequency of vehicle maintenance based on data on actual fuel consumption

The use of reasonable standards for the technical operation of motor vehicles is the key to improving the efficiency of the transport process. Due to the fact that a number of standards for the technical operation of vehicles have not been updated for many years, an urgent problem is the improvement of methods for rationing the technological parameters of the technical operation of vehicles. The purpose of the study is: improving the efficiency of the operation of motor vehicles based on the development and implementation of a methodology for adjusting the frequency of maintenance by the amount of actual fuel consumption. The approach proposed by the authors is based on the hypothesis that the work performed by the nodes and aggregates of vehicles is equivalent to the total fuel consumption. Therefore, the use of this parameter as an argument for the function of determining the frequency of preventive actions allows us to more fully take into account the operating conditions of vehicles, the nature of the transport work performed, technical, resource and design features. Methods of mathematical analysis and statistical processing of the results of field surveys were used to develop a methodology for adjusting the frequency of preventive effects by the amount of total fuel consumption. As a result of the work done: a new methodological approach to the appointment of the frequency of preventive actions by the amount of total fuel consumption is proposed; a methodology for adjusting the basic norms of the frequency of maintenance of motor vehicles based on data on actual fuel consumption is developed, which allows to establish the values of total fuel consumption that determine the need for preventive maintenance. The scientific novelty of the work is: – methodical approach to the appointment of the frequency of preventive actions by the amount of total fuel consumption; – methodology for determining the values of total fuel consumption, determining the need to perform preventive actions; – the values of the coefficient of reduction of fuel consumption when driving on a standard driving cycle to the conditions of traffic on the highway, defined for different categories of vehicles and necessary for the practical application of the developed methodology. The practical significance of the results of the study is determined by a new approach to the appointment of the frequency of maintenance, which allows more fully to take into account the actual operational factors affecting the resource characteristics of vehicles. Based on the results of practical application of the developed methodology, it was found that when operating KAVZ-4235 buses in the city, the frequency of TO-2 can be increased by 30%, and outside the suburban area by 45%. Based on the data obtained, recommendations have been developed for the practical application of the presented methods for correcting the regulatory periodicity of the total fuel consumption. Forecast calculations of the frequency of technical services of the categories of vehicles under consideration have been performed

A Computationally Efficient Framework for Modelling Energy Consumption of ICE and Electric Vehicles

This article proposes a novel framework to develop computationally efficient energy consumption models of electric and internal combustion engine vehicles. The number of calculations in a conventional energy consumption model prevents the model’s usage in applications where time is limited. As many fleet operators around the world are in the process of transitioning towards electric vehicles, a computationally efficient energy consumption model will be valuable to analyse the vehicles they trial. A vehicle’s energy consumption depends on the vehicle characteristics, drive cycles and vehicle mass. The proposed modelling framework considers these aspects, is computationally efficient, and can be run using open source software packages. The framework is validated through two use cases: an electric bus and a diesel truck. The model error’s standard deviation is less 5% and its mean is less than 2%. The proposed model’s mean computation time is less than 20 ms, which is two orders of magnitude lower than that of the baseline model. Finally, a case study was performed to illustrate the usefulness of the modelling framework for a fleet operator

The multi-objective Steiner pollution-routing problem on congested urban road networks

This paper introduces the Steiner Pollution-Routing Problem (SPRP) as a realistic variant of the PRP that can take into account the real operating conditions of urban freight distribution. The SPRP is a multi-objective, time and load dependent, fleet size and mix PRP, with time windows, flexible departure times, and multi-trips on congested urban road networks, that aims at minimising three objective functions pertaining to (i) vehicle hiring cost, (ii) total amount of fuel consumed, and (iii) total makespan (duration) of the routes. The paper focuses on a key complication arising from emissions minimisation in a time and load dependent setting, corresponding to the identification of the full set of the eligible road-paths between consecutive truck visits a priori, and to tackle the issue proposes new combinatorial results leading to the development of an exact Path Elimination Procedure (PEP). A PEP-based Mixed Integer Programming model is further developed for the SPRP and embedded within an efficient mathematical programming technique to generate the full set of the non-dominated points on the Pareto frontier of the SPRP. The proposed model considers truck instantaneous Acceleration/Deceleration (A/D) rates in the fuel consumption estimation, and to address the possible lack of such data at the planning stage, a new model for the construction of reliable synthetic spatiotemporal driving cycles from available macroscopic traffic speed data is introduced. Several analyses are conducted to: (i) demonstrate the added value of the proposed approach, (ii) exhibit the trade-off between the business and environmental objectives on the Pareto front of the SPRP, (iii) show the benefits of using multiple trips, and (iv) verify the reliability of the proposed model for the generation of driving cycles. A real road network based on the Chicago's arterial streets is also used for further experimentation with the proposed PEP algorithm. © 2019 Elsevier Lt

Understanding freight drivers’ behavior and the impact on vehicles’ fuel consumption and CO2e emissions

Despite the significant impact of driver behavior on fuel consumption and carbon dioxide equivalent (CO2e) emissions, this phenomenon is often overlooked in road freight transportation research. We review the relevant literature and seek to provide a deeper understanding of the relationship between freight drivers’ behavior and fuel consumption. This study utilizes a real-life dataset of over 4000 driving records from the freight logistics sector to examine the effects of specific behaviors on fuel consumption. Analyzed behaviors include harsh acceleration/deceleration/cornering, over-revving, excessive revolutions per minute (RPM), and non-adherence to legal speed limits ranging from 20 to 70 miles per hour (mph). Our findings confirm existing literature by demonstrating the significant impact of certain driving characteristics, particularly harsh acceleration/cornering, on fuel consumption. Moreover, our research contributes new insights into the field, notably highlighting the substantial influence of non-adherence to the legal speed limits of 20 and 30 mph on fuel consumption, an aspect not extensively studied in previous research. We subsequently introduce an advanced fuel consumption model that takes into account these identified driver behaviors. This model not only advances academic understanding of fuel consumption determinants in road freight transportation, but also equips practitioners with practical insights to optimize fuel efficiency and reduce environmental impacts

A review of recent advances in the operations research literature on the green routing problem and its variants

Since early 2010s, the Green Routing Problem (GRP) has dominated the literature of logistics and transportation. The problem itself consists of finding a set of vehicle routes for a set of customers while minimizing the detrimental effects of transportation activities. These negative externalities have been intensively tackled in the last decade. Operations research studies have particularly focused on minimizing the energy consumption and emissions. As a result, the rich literature on GRPs has already reached its peak, and several early literature reviews have been conducted on various aspects of related vehicle routing and scheduling problem variants. The major contribution of this paper is that it represents a comprehensive review of the current reviews on GRP studies. In addition to that, it is an up-to-date review based on a new chronological taxonomy of the literature. The detailed analysis provides a useful framework for understanding the research gaps for the future studies and the potential impacts for the academic community

Yeşil depo yeri belirleme ve araç rotalama problemlerinin GA ve sezgisel metotlarla çözülmesi : boya imalat firmasında uygulanması

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Yer seçimi ve rotalama problemleri, lojistik problemlerinin en önemli konularından olup farklı yaklaşımlarla ve çözüm yöntemleri ile geliştirilerek daha özel hale getirilmiş problemlerdir. Bu çalışmada verimlilik ve karlılık oranlarını arttırmak için bir boya firmasının lojistik biriminde, kara lojistiğinin en önemli problemlerinden olan depo yeri seçimi ve rotalama problemine farklı yaklaşımlarla çözümler aranmaktadır. İki farklı model önerilmiştir. İlk modelde şehirlerarası km'leri dikkate alarak çözüm yolu önerisi getirilmiştir. İkinci modelde ise çevreye karşı farkındalığı arttırmak için dünyada hızla artan küresel ısınmanın en önemli sebeplerinden olan sera gazlarından CO2 emisyon miktarlarını yolların eğimini dikkate alarak azaltan çözüm yolu önerisi getirilmiştir. Yer seçimi ve rotalama problemine, depo-yer seçimi ve atama problemi, kapasiteli araç rotalama problemi olmak üzere kademeli yaklaşım önerilmiştir. Birinci aşamada problem Mixed-Integer Linear Programming (MILP)'de çözülerek atama yapılmıştır. Sonuç olarak tüm şehirler uygun depolara tahsis edilmiştir. İkinci aşamada kapasiteli araç rotalama problemi sezgisel algoritma ve genetik algoritma yöntemleri kullanılarak çözülmüştür. Önerilen modeller Marmara Bölgesi'nde boya fabrikasında uygulanmıştır. Sonuç olarak önerilen genetik algoritmaların model 1 ve model 2'de klasik sezgisel yöntemden daha avantajlı olduğu sonucuna varılmıştır.Location and routing problems are one of the most important issues of logistics problems and solved using different approaches. In this study, location and routing problems were solved in a logistic department of a paint firm to increase the productivity and profitability rates. Two different models were proposed. The first model was only related with kms among cities. At the second model, in order to raise awareness on the environment, greenhouse gases that are one of the most important reasons of global warming in the world, was included into the model to reduce CO2 emissions by taking into account the inclination of roads. A hierarchical approach was proposed to solve these problems. At the first level, an assignment to problem (MILP) was solved. As a result, all the cities were assigned to proper storages. At the second level, capacitated routing problem was solved using a heuristic and genetic algorithm. The proposed models were applied in a real life paint factory, in Marmara region, Turkey. The results illustrate that the proposed genetic algorithm produced better result than the classical heuristic method for model 1 and model 2

Mathematical models and solution algorithms for the vehicle routing problem with environmental considerations

Urban freight distribution is essential for the functioning of urban economies. However, it is contributing significantly to problems such as traffic congestion and environmental pollution. The main goal of this research is to contribute to greening urban freight distribution by developing new mathematical models and solution algorithms pertaining to the two major steams in Vehicle Routing Problems (VRPs) with environmental considerations: (i) VRPs with an explicit fuel consumption estimation component as a proxy for emissions, and (ii) VRPs with vehicles in the fleet that run on a cleaner alternative fuel such as electricity. In the first stream, this thesis develops and solves a new realistic multi-objective variant of the pollution-routing problem, referred to as the Steiner Pollution-Routing Problem (SPRP), that is studied directly on the original urban roadway network. The proposed variant is capable of incorporating the real operating conditions of urban freight distribution, and striking a balance between traditional business and environmental objectives, while integrating all factors that have a major impact on fuel consumption, including the time-varying congestion speed, vehicle load, vehicle’s physical and mechanical characteristics, and acceleration and deceleration rates. The thesis develops new combinatorial results that facilitate problem solution on the original roadway network and also introduces new mathematical models for synthesizing the expected second-by-second driving cycle of a vehicle over a given road-link at a given time of the day. New efficient multi-objective optimisation heuristics are also developed for addressing realistic instances of the SPRP. On the other hand, in the latter stream discussed above, to tackle the significantly impeding problem of range anxiety in the face of goods distribution using Electric Commercial Vehicles (ECVs), a paradigm shift in the routing of ECVs is proposed by introducing the Electric Vehicle Routing Problem with Synchronised Ambulant Battery Swapping/Recharging (EVRP-SABS). The proposed problem exploits new technological developments corresponding to the possibility of mobile battery swapping (or recharging) of ECVs using a Battery Swapping Van (BSV). In the EVRP-SABS, routing takes place in two levels for the ECVs that carry out delivery tasks, and for the BSVs that provide the running ECVs with fully charged batteries on their route. There is, therefore, a need to establish temporal and spatial synchronisations between the vehicles in the two levels and to do so new combinatorial results and a new solution algorithm is proposed