Search results

The purpose of this study is to examine state-of-the-art in hybrid-electric propulsion system modeling and suggest new methodologies for sizing such advanced concepts. Many entities are involved in the modelling and design of hybrid electric aircraft; however, the highly multidisciplinary nature of the problem means that most tools focus heavily on one discipline and over simplify others to keep the analysis reasonable in scope. Correctly sizing a hybrid-electric system requires knowledge of aircraft and engine performance along with a working knowledge of electrical and energy storage systems. The difficulty is compounded by the multi-timescale dynamic nature of the problem. Furthermore, the choice of energy management in a hybrid electric system presents multiple degrees of freedom, which means the aircraft sizing problem now becomes not just a root-finding exercise, but also a constrained optimization problem.

The hybrid electric vehicle sizing problem can be sub-divided into three areas: modelling methods/fidelity, energy management and optimization technique. The literature is reviewed to find desirable characteristics and features of each area. Subsequently, a new process for sizing a new hybrid electric aircraft is proposed by synthesizing techniques from model predictive control and detailed conceptual design modelling. Elements from model predictive control and concurrent optimization are combined to formulate a new structure for the optimization of the sizing and energy management of future aircraft.

While the example optimization formulation provided is specific to a hybrid electric concept, the proposed structure is general enough to be adapted to any vehicle concept which contains multiple degrees of control freedom that can be optimized continuously throughout a mission.

The proposed technique is novel in its application of model predictive control to the conceptual design phase.

Recently, electric vehicles have been widely used in the cold chain logistics sector to reduce the effects of excessive energy consumption and to support environmental friendliness. Considering the limited battery capacity of electric vehicles, it is vital to optimize battery charging during the distribution process.

This study establishes an electric vehicle routing model for cold chain logistics with charging stations, which will integrate multiple distribution centers to achieve sustainable logistics. The suggested optimization model aimed at minimizing the overall cost of cold chain logistics, which incorporates fixed, damage, refrigeration, penalty, queuing, energy and carbon emission costs. In addition, the proposed model takes into accounts factors such as time-varying speed, time-varying electricity price, energy consumption and queuing at the charging station. In the proposed model, a hybrid crow search algorithm (CSA), which combines opposition-based learning (OBL) and taboo search (TS), is developed for optimization purposes. To evaluate the model, algorithms and model experiments are conducted based on a real case in Chongqing, China.

The result of algorithm experiments illustrate that hybrid CSA is effective in terms of both solution quality and speed compared to genetic algorithm (GA) and particle swarm optimization (PSO). In addition, the model experiments highlight the benefits of joint distribution over individual distribution in reducing costs and carbon emissions.

The optimization model of cold chain logistics routes based on electric vehicles provides a reference for managers to develop distribution plans, which contributes to the development of sustainable logistics.

In prior studies, many scholars have conducted related research on the subject of cold chain logistics vehicle routing problems and electric vehicle routing problems separately, but few have merged the above two subjects. In response, this study innovatively designs an electric vehicle routing model for cold chain logistics with consideration of time-varying speeds, time-varying electricity prices, energy consumption and queues at charging stations to make it consistent with the real world.

The aim of this study is to identify and describe the factors associated with Nissan Company's electric vehicle (EV) development. In addition, Nissan's different commercialization strategies toward EV and HEV development will be discussed.

This study uses a descriptive case study approach to provide a deep understanding of successful or failed projects of Nissan. In this term, the company's green car development between 1996 and 2012 will be analyzed. Based on the market presence, Nissan's electric vehicle production trend is divided into two different generations with different characteristics. The gap between these two generations has a structural effect on the current state of Nissan's EV development.

One key factor behind Nissan's success and lead in the current electric vehicle market is the long-term experience with specific type of market structure, which has nurtured the company with a strong green vehicle development capability. The study shows that the electric vehicles market gap acted as a catalyst for later Nissan's successful cases. Also, the authors demonstrate how the dramatic shifts in Nissan strategies helped the company to revitalize its leadership as an electric car guru.

This study provides a better insight into the importance of early stage commercialization strategies in the re-born market of eco-friendly vehicles.

This paper aims to address the broad question of how organizations capture value from foresight exercises. Through a comparative case analysis, this paper looks at what firms do to make the information usable and create value. It explores factors that cause different firms to respond differently to the same trends. It analyzes the passenger car segment of the automobile industry and the response of six major firms to fossil fuel and changing environmental regulations through an analysis of their policies and strategic activities, such as new product development. It finds foresight to be an important link between firm capabilities and environmental changes.

This paper adopts the case approach to capture the linkage between the issue and the context (Yin, 1994) and uses multiple cases to explore the variables by comparing and contrasting the cases on key aspects (Eisenhardt and Graebner, 2007). As the paper ' s objective is to understand the similarities and differences between dominant firms in the sector, it chooses through theoretical sampling, six firms that have a presence in all the major regions of the world – two each from the USA, Europe and Japan – Ford, General Motors, Volkswagen, Renault, Toyota and Honda. This sample represents the firms and regions traditionally strong in the passenger car industry.

Thus, it is seen that the relationship that was posited in the conceptual model between the goal of the firms, the vision of the future and the nature of products and approach to technology/competence development seems to be valid. However, in addition, the paper perceives that some additional linkages that link between foresight and the goals and vision of the future seem to be influenced by the extent of uncertainty. In addition, the decisions regarding portfolio of products and approaches to technology and competence development seem to be also influenced by the perception of existing competencies and the external competitive context.

This paper was based on multiple cases created out of secondary information, hence the constructs used are those which are perceived and stated.

The paper could help firms understand decisions related to technology choices in field involving high levels of uncertainty and competition.

This paper could improve learning processes from foresight exercises, and enable strategic decisions to be taken on these.

Thus, this paper has explored the linkages between what firms perceive and state, and what is reflected in their actions. It has looked at this linkage from the perspective of foresight, and the strategic perspective of the firm. It has come up with additional issues and questions that influence this relationship. These can inform future research in this domain.

The purpose of this paper is to investigate the diffusion dynamics of electric and hybrid commercial vans and its enabling factors in the city logistics (CL) contexts. The case of parcel delivery in Torino, Italy, is considered. Attention is paid to the influence on the choice of low impact vehicles of not only public strategies but also operational aspects characterizing urban freight distribution systems.

A System Dynamics model based on the Bass diffusion theory computes the number of adopters of low-emission vehicles together with the quantity of vans required and the associated economic savings. The model includes variables about freight demand, delivery frequency, van carrying capacity, routes, stops, distances traveled, and vehicle charging stations. A sensitivity analysis has been completed to identify the main diffusion levers. The focus is on advertising and other drivers, such as public contributions, taxes traditional polluting vehicles are subjected to, as well as on routing optimization strategies.

Advertising programs, green image, and word-of-mouth drive market saturation, although in a long time period. In fact, low-impact vehicles do not offer any economic advantage over traditional ones requiring higher investment and operating costs. Public incentives to purchase both green vehicles and charging stations, together with carbon taxes and a congestion charge affecting polluting vehicles, are able to shorten the adoption time. In particular, public intervention reveals to be effective only when it unfolds through a number of measures that both facilitate the use of environmentally friendly vehicles and discourage the adoption of traditional commercial vans. Route optimization also hastens the complete market saturation.

This work fosters research about the mutual relationships between the diffusion of low-emission commercial vehicles and the operational and contextual CL factors. It provides a structured approach for investigating the feasibility of innovative good vehicles that might be part of assessments of CL measures and requirements. Finally, the model supports studies about the cooperation among stakeholders to identify effective commercial vehicle fleets.

This study fosters collaboration among CL players by providing a roadmap to identify the key factors for the diffusion of environmentally friendly freight vehicles. It also enables freight carriers to assess the operational and economic feasibility of adopting low-impact vehicles. Finally, it might assist public authorities in capturing the effects of new urban transportation policies prior to their implementation.

Most of the current CL literature defines policies and analyzes their effects. Also, there are several contributions on the diffusion of low emission cars. The present study is one of the first works on the diffusion of low-impact commercial vehicles in urban areas by considering the associated key operational factors. A further value is that the proposed model combines operational variables with economic and environmental issues.

Velomobiles or bicycles cars are human-powered vehicles, enclosed for improving aerodynamic performance and protection from weather and collisions. The purpose of this paper is to design and develop a three-wheeled velomobile equipped with a hybrid human-electric propulsion system.

The mechanical layout has been developed in order to improve safety, a CAD code has been used for the design and the dynamic performances have been studied by means of specific multi-body codes. The electric propulsion system has been designed both with analytical and FEM methods.

A special three-wheeled tilting vehicle layout equipped with a four-bar linkage connection has been developed. A particular synchronous reluctance machine has been developed, which is very suitable for human-electric hybrid propulsion. A MATLAB code for integrated mechanical and electrical analysis has been developed.

A new kind of light vehicle has been conceived. A new synchronous reluctance machine with high efficiency has been developed. A performance analysis in electric, human and hybrid working modes has been presented, which takes into account the specific features of both the electric motor and the pedaling legs. A prototype of the vehicle has been built.

The purpose of this paper is the investigation of the main aspects of optimal reliability allocation with respect to the design of hybrid electric vehicles. In particular, with reference to the hybrid electric vehicle propulsion system, the problem of data uncertainty, due to a scarce knowledge of the components' reliabilities, is taken into account. This problem is crucial for new technology systems and it is faced with a Bayesian approach: components' reliabilities are considered as random variables, characterised in the paper by negative log‐gamma distributions.

The main aspects of optimal reliability allocation with the design of hybrid electric vehicles are presented, pointing out the opportunity of a reliability evaluation in the planning stage.

The topic of a series hybrid vehicle reliability is addressed, nevertheless results can be easily extended to the parallel configuration. In particular, the opportunity of a reliability evaluation of the propulsion system in the design stage is highlighted, mainly when new technology components are involved.

The value of the paper consists in the methodology allowing to express the system reliability uncertainty as a function of component uncertain data. Then, as far as concern the practical implications, the optimal allocation of the components' reliabilities can be efficiently performed, in order to minimise the system total cost respecting a prefixed value of the system reliability. In the final part of the paper, a numerical application, related to a series hybrid electric vehicle propulsion system, is presented to show the feasibility of the approach.

Purpose – Electric vehicles are very topical in developed countries. The breakthrough of new battery technologies and changing conditions driven by climate policy and growing fossil fuel prices has caused all major car manufacturing countries in the developed world to initiate R&D programmes to gain competitive advantage and to foster market diffusion of electric vehicles (EVs). This chapter looks at developments in China and compares them with observations from developed countries to draw conclusions about differences in their future paths of development.

Methodology – This chapter escribes the potentials and R&D approaches for different types of EVs in developing countries, using China as example, in comparison with developed countries. It looks at innovation strategies, policy framework and potential diffusion of EVs.

Findings – Market diffusion strategies in developed countries and China may differ, since, in the former manufacturers try to implement a premium strategy (i.e. offer high-price sophisticated EVs), while in the latter market, diffusion will probably appear at the lower end of vehicle types, i.e. via electric scooters and small urban vehicles. It is concluded that the market introduction strategies of EVs in developing countries and developed countries could converge because signs of downsizing of vehicles can be observed in the developed world, while upscaling from bikes and electric scooters can be expected for China, so that large-scale market introduction could occur via small city cars.

Implications for China – Instead of following the Western motorisation path, an option for China could be to develop a new one-stop-shop mobility concept integrating small EVs into such a concept.

The purpose of this paper is to optimize the design and power management control fuel cell/supercapacitor and fuel cell/battery hybrid electric vehicles and to provide a comparative study between the two configurations.

In hybrid electric vehicles (HEVs), the power flow control and the powertrain component sizing are strongly related and their design will significantly influence the vehicle performance, cost, efficiency and fuel economy. Hence, it is necessary to assess the power flow management strategy at the powertrain design stage in order to minimize component sizing, cost, and the vehicle fuel consumption for a given driving cycle. In this paper, the PSO algorithm is implemented to optimize the design and the power management control of fuel cell/supercapacitor (FC/SC) and fuel cell/battery (FC/B) HEVs for a given driving cycle. The powertrain and the proposed control strategy are designed and simulated by using MATLAB/Simulink. In addition, a comparative study of fuel cell/supercapacitor and fuel cell/battery HEVs is analyzed and investigated for adequately selecting of the appropriate HEV, which could be used in industrial applications.

The results have demonstrated that it is possible to significantly improve the hydrogen consumption in fuel cell hybrid electric vehicles (FCHEVs) by applying the PSO approach. Furthermore, by analyzing and comparing the results, the FC/SC HEV has slightly higher fuel economy than the FC/B HEV.

The addition of electrical energy storage such as supercapacitor or battery in fuel cell‐based vehicles has a great potential and a promising approach for future hybrid electric vehicles (HEV). This paper is mainly focused on the optimal design and power management control, which has significant influences on the vehicle performance. Therefore, this study presents a modified control strategy based on PSO algorithm (CSPSO) for optimizing the power sharing between sources and reducing the components sizing. Furthermore, an interleaved multiple‐input power converter (IMIPC) is proposed for fuel cell hybrid electric vehicle to reduce the input current/output voltage ripples and to reduce the size of the passive components with high efficiency compared to conventional boost converter. Meanwhile, the fuel economy is improved. Moreover, a comparative study of FC/SC and FC/B HEVs will be provided to investigate the benefits of hybridization with energy storage system (ESS).

A hybrid-electric unmanned aerial vehicle (HE-UAV) model has been developed to address the problem of low endurance of a small electric UAV. Electric-powered UAVs are not capable of achieving a high range and endurance due to the low energy density of its batteries. Alternatively, conventional UAVs (cUAVs) using fuel with an internal combustion engine (ICE) produces more noise and thermal signatures which is undesirable, especially if the air vehicle is required to patrol at low altitudes and remain undetected by ground patrols. This paper aims to investigate the impact of implementing hybrid propulsion technology to improve on the endurance of the UAV (based on a 13.6 kg UAV).

A HE-UAV model is developed to analyze the fuel consumption of the UAV for given mission profiles which were then compared to a cUAV. Although, this UAV size was used as reference case study, it can potentially be used to analyze the fuel consumption of any fixed wing UAV of similar take-off weight. The model was developed in a Matlab-Simulink environment using Simulink built-in functionalities, including all the subsystem of the hybrid powertrain. That is, the ICE, electric motor, battery, DC-DC converter, fuel system and propeller system as well as the aerodynamic system of the UAV. In addition, a ruled-based supervisory controlled strategy was implemented to characterize the split between the two propulsive components (ICE and electric motor) during the UAV mission. Finally, an electrification scheme was implemented to account for the hybridization of the UAV during certain stages of flight. The electrification scheme was then varied by changing the time duration of the UAV during certain stages of flight.

Based on simulation, it was observed a HE-UAV could achieve a fuel saving of 33% compared to the cUAV. A validation study showed a predicted improved fuel consumption of 9.5% for the Aerosonde UAV.

The novelty of this work comes with the implementation of a rule-based supervisory controller to characterize the split between the two propulsive components during the UAV mission. Also, the model was created by considering steady flight during cruise, but not during the climb and descend segment of the mission.