[en] Highlights: • The interactive mechanism between system and PHEVs is presented. • The charging load self-management without sacrificing user requirements is proposed. • The charging load self-management is coupled to system operation risk analysis. • The charging load self-management can reduce the extra risk brought by PHEVs. • The charging load self-management can shift charging power to the time with low risk. - Abstract: Many jurisdictions around the world are supporting the adoption of electric vehicles through incentives and the deployment of a charging infrastructure to reduce greenhouse gas emissions. Plug-in hybrid electric vehicles (PHEVs), with offer mature technology and stable performance, are expected to gain an increasingly larger share of the consumer market. The aggregated effect on power grid due to large-scale penetration of PHEVs needs to be analyzed. Nighttime-charging which typically characterizes PHEVs is helpful in filling the nocturnal load valley, but random charging of large PHEV fleets at night may result in new load peaks and valleys. Active response strategy is a potentially effective solution to mitigate the additional risks brought by the integration of PHEVs. This paper proposes a power system operation risk analysis framework in which charging load self-management is used to control system operation risk. We describe an interactive mechanism between the system and PHEVs in conjunction with a smart charging model is to simulate the time series power consumption of PHEVs. The charging load is managed with adjusting the state transition boundaries and without violating the users’ desired charging constraints. The load curtailment caused by voltage or power flow violation after outages is determined by controlling charging power. At the same time, the system risk is maintained under an acceptable level through charging load self-management. The proposed method is implemented using the Roy Billinton Test System (RBTS) and several PHEV penetration levels are examined. The results show that charging load self-management can effectively balance the extra risk introduced by integration of PHEVs during the charging horizon

[en] What makes consumers adopt energy-sustainable innovations? The uptake of such products and technologies is of importance, particularly at a time when climate change, diminishing energy resources and energy security are urgent issues. This paper reports on a case study of consumer adoption of hybrid vehicles, a green innovation that has been in the market since the late 1990s. The study is based on a questionnaire survey, conducted in 2009 in collaboration with Toyota GB, to investigate the dimensions that constitute motivations to purchase the Prius and to examine how policy can encourage hybrid adoption. The survey yielded 1484 responses, 1263 of which were used for the analysis; the results of the exploratory factor analyses provide information on consumer purchase motivations. The financial benefits related to transport policy are an important factor in consumer hybrid purchase motivations, and social norms and consumers' willingness to comply with the norms of their groups influence the purchase decision. We also find that various meanings are attached to hybrid vehicle ownership, and practical, experiential and affective values need to be communicated to consumers in terms of value added.

[en] Highlights: • Torsional vibration of Parallel HEV start condition is studied. • Optimum model of the Parallel HEV powertrain is established. • Torque of the Parallel HEV powertrain is decreased by optimization method. • Simulation optimized results are verified by experiments. One of the major issues for Parallel Hybrid Electric Vehicle (Parallel HEV) powertrain is the torsional vibration in the process of start condition, which is unavoidable. This article targets at reducing the damage caused by the torsional vibration with the method of Multi-Objective Optimization (MOO). The dynamic model of the parallel HEV powertrain is established by lumped mass method. Five design variables are selected from 19 parameters by the process of Design of Experiment (DOE), and are optimized by multi-objective downhill simplex optimization algorithm. Pareto Frontier is used to describe the relationship between the two objective functions, and one of the optimization data serves as the basics data for the powertrain modification. Finally, the results of optimization before and after optimization are compared by the test bench. Experimental results under the start condition show that the maximum torque of the optimized powertrain is decreased within the safe range, and the problem of shaft breaking on the originally powertrain is solved.

[en] Research highlights: → Energy conversion phenomena of PHEVs for different drive cycles and depletion rates of energy sources. → Detailed physically based framework for analyzing energy conversion phenomena in PHEVs. → Interaction of energy flows and energy losses with energy consumption of the PHEV. → Identification and explanation of mechanisms leading to optimal tank-to-wheel efficiency. → Analysis of well-to-wheel efficiencies for different realistic well-to-tank scenarios. -- Abstract: Energy flows and energy conversion efficiencies of commercial plug-in hybrid-electric vehicles (PHEV) are analyzed for parallel and series PHEV topologies. The analysis is performed by a combined analytical and simulation approach. Combined approach enables evaluation of energy losses on different energy paths and provides their impact on the energy consumption of the PHEV. Thereby the paper reveals energy conversion phenomena of different PHEV topologies operating according to charge depleting and charge sustaining modes as well as according to different test cycles. It is shown in the paper that amount of the energy depleted from both on-board energy sources is significantly influenced by the efficiencies of energy conversion chains from on-board energy sources to the wheels. It is also shown that energy used to power the PHEV according to particular test cycles varies based on its operating mode, which influences energy flows on different energy paths within the PHEVs and consequently overall energy consumed by the PHEV. The paper additionally discusses well-to-wheel efficiencies considering different realistic well-to-tank scenarios. It is shown that well-to-tank efficiency of electric energy generation significantly influences optimal operating mode of the PHEV if consumption of primary energy sources is considered.

[en] Highlights: • Innovative hybrid powertrain system using a planetary gearset and dual one-way clutch. • Three operation modes: EV-mode, engine-driven mode and power split e-CVT mode. • Outstanding energy improvement (max. 32+%) compared to traditional vehicles. • Experimentally implemented for light-duty vehicles in the near future. - Abstract: The power split electronic-continuously variable transmission (e-CVT) has been globally accepted as a main architecture for developing a hybrid electric vehicle (HEV). In this paper, a novel full hybrid electric motorcycle with power split e-CVT is proposed. It consists of an engine, a reversible generator, a reversible driving motor, a set of the planetary gear, two one-way clutches, and transmission components arranged for a planetary gearset and dual one-way clutch transmission (PDOC). Three operation modes were properly switched for optimal output dynamics: EV-mode, engine-driven mode, and power split e-CVT mode. Performance simulation compared with that of a baseline system using the conventional rubber-belt CVT is conducted to evaluate its feasibility and potential. The results present superior driving performance and fuel economy for the proposed motorcycle (maximum 32% fuel economy improvement) and thus offer a favorable support for further development

[en] State and alternative fuel provider fleets are updated on DOE's position on HEVs and LSVs

[en] Highlights: • Data driven hierarchical control is presented for online energy management. • The upper state-of-charge planner is employed for planning battery state-of-charge. • The lower powertrain controller is applied to regulate the engine operation. • The strategy can achieve better resilience to “unseen” driving patterns. • The strategy is proven to be a real-time implementable, close-to-optimal solution. The pre-determined city bus routes and the availability of partial-trip information obtained through vehicular connectivity provides new opportunities for plug-in vehicles to plan electric energy reasonably. This paper presents a data-driven hierarchical control method for online energy management of plug-in hybrid electric city buses, which can learn from globally optimal solutions based on historical accumulated cycles while taking advantage of connectivity-enabled partial-trip information. The devised scheme comprises two levels of control modules. The upper battery state-of-charge planner trained using historical optimal data is employed for deriving a reference state-of-charge based on the current battery state, remaining trip length, and low/high speed ratios. The lower powertrain controller is then applied to regulate the engine operation according to the reference state-of-charge and powertrain states. This article presents two contributions: (1) both accumulated historical optimal data and partial-trip information are assimilated to augment the applicability of the control hierarchy, thus achieving better resilience to “unseen” driving patterns; (2) given limited resources of micro-controllers, the control strategy is proven to be a real-time implementable, close-to-optimal solution. A variety of results show that the proposed approach can achieve significant fuel savings (4.99%–14.80%) as compared to the charge depleting and charge sustaining strategy.

[en] This paper describes a number of different allocation methods for assigning greenhouse gas emissions from electricity generation to charging plug-in electric vehicles. These methods for calculating the carbon intensity of electricity are discussed in terms of merits and drawbacks and are placed into a framework to aid in understanding the relation with other allocation methods. Three independent decisions are used to define these methods (average vs. marginal, aggregate vs. temporally-explicit, and retrospective vs. prospective). This framework is important because the use of different methods can lead to very different carbon intensities and studies or analyses that do not properly identify the methods used can confuse policymakers and stakeholders, especially when compared to other studies using different methods. - Highlights: • Reviews literature of emissions from charging electric vehicles. • Examines multiple allocation methods for GHG emissions for electric vehicles. • Provides a framework for understanding various GHG impact studies. • A “best” allocation method for all situations and analyses does not exist

[en] Although energy consumption in the industry sector has almost been stable, energy consumption in the transportation (passenger and freight) sector has increased much after the oil crisis. The increase of energy consumption in the passenger sector can be attributed to the increase in transportation by private passenger vehicles; while the increase in the freight sector was due to the modal shift to trucks. Among transportation methods, automobiles, i.e. passenger vehicles and trucks, are now dominant in terms of energy consumption and also in terms of amount of transportation. Therefore implementing energy conservation measures relating to automobiles is very important in order to suppress the energy consumption in the transportation sector. This report summarizes the results of investigation on energy conservation measures, especially relevant to automobiles. It was found from the investigation that most promising and effective technologies or measures are promoting market penetration of vehicles satisfying ''top runner standard'', development and employment of hybrid vehicles, and introduction of vehicles with ''idling-stop'' systems. (author)

[en] Plug-in hybrid electric vehicles (PHEVs) represent one option for the electrification of private mobility. In order to efficiently integrate PHEVs into power systems, existing organizational structures need to be considered. Based on procedures of power systems planning and operation, actors are identified whose operational activities will be affected by PHEV integration. Potential changes and challenges in the actors' long- and short term planning activities are discussed. Further, a PHEV operation state description is developed which defines vehicle operation states from the power system point of view integrating uncontrolled, controlled recharging and vehicle to grid (V2G) utilization in one single framework. Future PHEV managing entities, such as aggregators, can use this framework for planning and operation activities including load management and V2G. This operational state description could provide a solution for future short term planning challenges of PHEVs and an aegis for various routes of current research, which to date have been weakly linked to each other.