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State-of-the-art Modelica tools for modelling and simulating multi-physical systems have reached certain maturity among the building physics community. Hence, simulation is widely used for control, sizing and performance assessment of energy systems. However, serious efficiency issues arise for large-scale models. This article proposes a practical application of co-simulation methods on detailed district energy systems. The aim of this study is to assess performance and scalability of co-simulation through functional mock-up interfaces on a detailed and multi-physical district model. In particular, we propose a comparative analysis between classical simulation and co-simulation methods and a scalability analysis on a growing number of buildings. The models have been implemented using Modelica language and the OpenIDEAS library. A decomposition approach is taken for modelling the entire system, while stochasticity in the inputs is taken into account. Results are presented for various integration scenarios, including a classical integrated simulation for reference and co-simulations involving different master-algorithms within Dymola and DACCOSIM 2017. Scenarios are compared in terms of speed-up and accuracy of principal physical quantities representing key performance indicators such as indoor temperature, current and voltage at building's connection. The analysis shows that co-simulation can run up to 90 times faster than the integrated simulation for 24 buildings, while ensuring acceptable accuracy. [ABSTRACT FROM AUTHOR]

Hybrid electrical vehicles involve two sources of energy, usually gasoline and electricity. The energy management determines the power sharing between the internal combustion engine and the electrical machine (EM). It is highly dependent on the driving cycle (i.e. the use of the vehicle). In this context, the optimal sizing of the EM is determined by: the driving cycle, the power-train characteristics (i.e. ratios and physical limitations e.g. maximum torque available) and the energy management. The key idea of this work is to involve the driving cycle and the environment of the electrical machine in a global multi-objective optimization process taking into account an optimal energy management and an accurate model of the EM based on magnetic circuit equivalent model. [ABSTRACT FROM AUTHOR]

A way to improve existing hybrid vehicles is by globally optimizing the design of their components in relation to their actual use. This paper proposes a global optimal design method for power-split hybrid electric vehicles (PS-HEVs) equipped with an electric variable transmission (EVT). A genetic algorithm is used to optimize system parameters. The process includes discrete dynamic programming (DDP) for optimal energy management. The optimization focuses on minimizing fuel consumption and the number of battery cells. Pareto fronts are depicted and compared for different drive cycles, and they show the existence of a possible tradeoff between fuel consumption and battery size. [ABSTRACT FROM AUTHOR]

Automotive engineers and researchers have proposed different topologies for series–parallel hybrid electric vehicles (SP-HEVs). The Toyota Hybrid System (THS) is the best known SP-HEV-based vehicle, but alternative solutions, such as electric variable transmission (EVT), have been also proposed. An efficient comparison between these different solutions is a key point to estimate the added value of each topology. This paper presents the application of optimal control to two series–parallel hybrid architectures for efficiency assessment purposes. The dynamic programming method is applied to the THS and to a virtual hybrid vehicle with an EVT. The way to take into account the supplementary degree of freedom provided by the decoupling of the wheels and the engine in both topologies is presented. The optimal fuel consumption is then compared on different driving cycles and brings out an overconsumption of the EVT topology. Then, a parametric study shows that inserting an appropriate gear ratio on the internal-combustion-engine (ICE) shaft can improve the EVT efficiency that becomes close to the THS efficiency. [ABSTRACT FROM PUBLISHER]

Fuel consumption of a hybrid electrical vehicle (HEV) depends on the driving cycle (i.e. the use of the vehicle), on the powertrain components and on the energy management. The paper proposes an optimal component sizing process taking into account the entire system. An optimal energy management is used in order to minimize the fuel consumption on a driving cycle. This optimization approach of the HEV uses Radial Basis Function models which allow a fast constrained optimization. [ABSTRACT FROM AUTHOR]

Photovoltaic water pumping systems (PVWPS) are a promising solution to improve domestic water access in low-income rural areas. It is challenging, however, to make them more affordable for the local communities. We develop here a comparative methodology to assess relevant features of both widely employed PVWPS architecture with water tank storage, and hardly used PVWPS architecture with a battery bank instead of tank storage. The quantitative comparison is carried out through techno-economic optimization, with the goal of minimizing the life cycle cost of PVWPS with constraints on the satisfaction of the water demand of local inhabitants and on the groundwater resource sustainability. It is aimed to support decision-makers in selecting most appropriate storage for domestic water supply projects. We applied the methodology in the rural village of Gogma, Burkina Faso. Results indicate that the life-cycle cost of an optimized PVWPS with batteries is $24.1k while it is $31.1k if a tank is used instead. Moreover, reduced impact on groundwater resources and greater modularity to adapt to evolving water demand is noted if using batteries. However, as batteries must be replaced regularly and recycled adequately, PVWPS' financial accessibility could increase only if sustainable and efficient operation, maintenance, and recycling facilities for batteries were present or developed locally. [ABSTRACT FROM AUTHOR]