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Hybrid technology in marine vehicles can significantly reduce fuel consumption and local CO 2 emissions. It has been applied successfully to several ship-types, mostly with conventional, rule-based, strategies. To further improve performance, intelligent control strategies are necessary. This work, inspired by automotive research in Energy Management Strategies, applies the Equivalent Consumption Minimisation Strategy (ECMS) to a ship powered by a hybrid propulsion plant with hybrid power supply that can be recharged with renewable shore power. This hybrid configuration has the additional challenge to determine the optimal power-split between three or more different power sources, in real-time, and to optimally deplete the battery packs over the mission profile. To this end, a Mixed-Integer Non-Linear optimisation Problem is formulated and solved by combining Branch & Bound and Convex optimisation. Dynamic Programming (DP) is used to benchmark the real-time strategies, which are also compared to the current rule-based (RB) controller. Simulation results of a case study tugboat with validated models show that, with unknown load demand, 6% additional fuel savings can be achieved with ECMS. [ABSTRACT FROM AUTHOR]

The combination of electric motors and internal combustion engines in hybrid electric vehicles (HEV) can considerably improve the fuel efficiency compared to conventional vehicles. In order to use its full potential, a predictive intelligent control system using information about impending driving situations has to be developed, to determine the optimal gear shifting strategy and the torque split between the combustion engine and the electric motor. To further increase fuel efficiency, the vehicle velocity can be used as an additional degree of freedom and the development of a predictive algorithm calculating good choices for all degrees of freedom over time is necessary. In this paper, an optimization-based algorithm for combined energy management and economic driving over a limited horizon is proposed. The results are compared with results from an offline calculation, which determine the overall fuel savings potential through the use of a discrete dynamic programming algorithm. [ABSTRACT FROM AUTHOR]

Abstract: There are many approaches addressing the problem of optimal energy management in hybrid electric vehicles; however, most of them optimise the control strategy for particular driving cycles. This paper takes into account that the driving cycle is not a priori known to obtain a near-optimal solution. The proposed method is based on analysing the power demands in a given receding horizon to estimate future driving conditions and minimise the fuel consumption while cancelling the expected battery energy consumption after a defined time horizon. Simulations show that the proposed method allows charge sustainability providing near-optimal results. [Copyright &y& Elsevier]

Abstract: Hybrid electric vehicles require an algorithm that controls the power split between the internal combustion engine and electric machine(s), and the opening and closing of the clutch. Optimal control theory is applied to derive a methodology for a real-time optimal-control-based power split algorithm. The presented strategy is adaptive for vehicle mass and road elevation, and is implemented on a standard Electronic Control Unit of a parallel hybrid electric truck. The implemented strategy is experimentally validated on a chassis dynamo meter. The fuel consumption is measured on 12 different trajectories and compared with a heuristic and a non-hybrid strategy. The optimal control strategy has a fuel consumption lower (up to 3%) than the heuristic strategy on all trajectories that are evaluated, except one. Compared to the non-hybrid strategy the fuel consumption reduction ranged from 7% to 16%. [Copyright &y& Elsevier]

Abstract: The paper focuses on investigating thermal-transients effects, associated to intermittent use of internal combustion engine (ICE), on fuel economy and hydrocarbon (HC) emissions of series hybrid solar vehicles (HSVs). An offline, non-linear constrained optimization is set-up to individuate the ICE power trajectory that simultaneously minimizes fuel consumption, suitably operates the battery and fully exploits daily solar contribution. The results highlight the importance of including thermal transients in HSV energy management. The combined effects of engine, generator and battery losses, along with cranking energy and thermal transients, produce non-trivial solutions for the engine/generator group, which should not necessarily operate at its maximum efficiency. [Copyright &y& Elsevier]

This paper deals with power flow management within a hybrid fuel cell-powered vehicle during real-time operation. The aim is the real-time control of the power distribution between the fuel cell and its associated energy storage to optimize the global hydrogen consumption while maintaining drivability. An original concept to convert the electrical power flow into equivalent hydrogen cost is proposed. On that basis, the previously developed control strategy (the equivalent consumption minimization strategy) is used to determine the real-time optimal power distribution by simple minimization of a univariate form. The approach presented has been applied to and implemented on a real fuel cell-supercapacitor-powered vehicle. Experimental and simulation results are presented, demonstrating that this approach provides an improvement of fuel efficiency along with robustness and ease of implementation. [Copyright &y& Elsevier]

This paper presents a fuzzy-logic-based energy management and power control strategy for parallel hybrid vehicles (PHV). The main objective is to optimize the fuel economy of the PHV, by optimizing the operational efficiency of all its components. The controller optimizes the power output of the electric motor/generator and the internal combustion engine by using vehicle speed, driver commands from accelerator and braking pedals, state of charge (SOC) of the battery, and the electric motor/generator speed. Separate controllers optimize braking and gear shifting. Simulation results show potential fuel economy improvement relative to other strategies that only maximize the efficiency of the combustion engine. [Copyright &y& Elsevier]