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The most used type of the secondary energy sources is the lead-acid accumulator today. It is also used as a propulsion in hybrid electric vehicles. Functional principle stayed same as in foundation time, only parameters are still improving. Lifetime of lead-acid accumulator is influenced by used separator. The work deals with the description of properties of lead acid separators, methods of testing and evaluation of the suitability for use.

This work aims on acumulators for hybrid vehicles and deals particularly with research of inner-resistance of the lead-acid batteries. There is a brief characterization of hybrid cars in first part of the tesis. Second part is dealing with design of experimental measurement setup for measurement of lead-acid electrochemical cells. Set of experiments on several cells was performed, description of experiments and results in graphical form are present.

Hybrid electric vehicles use lead acid batteries operating under partial charge. Battery life of these batteries is dependent on the speed of development of lead sulphate (PbSO4) to the negative electrodes. Different admixtures are affected battery life. This work deals with the influence of titanium dioxide on the negative active material in lead battery. Mainly devoted to the influence of the applied pressure.

Lead-acid batteries are most used secondary electrochemical power sources. Their basic principle has remained the same for several years; only the operating parameters are in development. Lead-acid batteries are used in hybrid electric vehicles (HEV), which operates in the partial charge PSoC. Sulphation is one of the possible failures lead-acid batteries in the HEV, especially the negative electrode. By adding additives to the negative active mass can reduce the rate of sulphation and increase ability to accept an electrical charge by negative electrode.

In this work is proposed the generalized powertrain of the parallel hybrid car. The powertrain is composed from the sub-models of the power sources. Each sub-model is described by the quasi-static modeling. For given routes is computed the power demand. Based on the derived power demand, three energy management systems are tested. First system is based on heuristic rules. The second one use more sophisticated control algorithms - the optimization method. Main idea is based on minimum principle, when the control algorithm tries to minimize the cost function (fuel use, emission). The last one is based on the equivalent consumption minimization strategy.

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In early design phase for new hybrid electric vehicle (HEV) powertrains, simulation isused for the estimation of vehicle fuel consumption. For hybrid electric powertrains,fuel consumption is highly related to powertrain efficiency. While powertrainefficiency of hybrid electric powertrain is not a linear product of efficiencies ofcomponents, it has to be analysed as a sequence of energy conversions includingcomponent losses and energy interaction among components.This thesis is aimed at studying the energy losses and flows and present them in theform of Sankey diagram, later, an adaptive energy management system is developedbased on current rule-based control strategy. The first part involves developing energycalculation block in GT-SUITE corresponding to the vehicle model, calculating allthe energy losses and flows and presenting them in Sankey diagram. The secondpart involves optimizing energy management system control parameters according todifferent representative driving cycles. The third part involves developing adaptiveenergy management system by deploying optimal control parameter based on drivingpattern recognition with the help of SVM (support vector machine).In conclusion, a sturctured way to generate the Sankey diagram has been successfullygenerated and it turns out to be an effective tool to study HEV powertrain efficiencyand fuel economy. In addition, the combination of driving pattern recognition andoptimized control parameters also show a significant potential improvement in fuelconsumption. / Under den tidiga utvecklingsfasen av nya elektrifieradedrivlinor for hybridapplikationer (HEV) används simulering för uppskattning avfordonets bränsleförbrukning. För dess drivlinor är bränsleförbrukningen i hög gradkopplad till drivlinans verkningsgrad. Även om drivlinans verkningsgrad inte ären linjär prokukt av komponenternas verkningsgrad behöve rden analyseras somen sekvens av energiomvandlingar, inklusive förluster och energipåverkan mellankomponenter.Detta examensarbete syftar till att undersöka energiförluster och flöden samtpresentera dessa i form av sankey diagram. Senare utvecklas ett anpassningsbartenergihanteringssystem baserat på nuvarande regelbaserad kontrollstrategi. Deninledande delen involverar utvecklandet av energianalys i GT-SUITE som motsvararfordonsmodellen, beräkningar av totala energiförluster och flöden samt presentationav dessa i ett sankey diagram. Den andra delen innefattar optimering avenergihanteringssystems kontrollparametrar enligt olika representativa körcykler.Den tredje delen involverar utveckling av anpassningsbara energihanteringssystemgenom användning av optimala kontrollparameterar baserad på detektering avkörbeteende med hjälp av SVM ( stödvektormaskin).Slutligen, ett strukturerat sätt att generera sankey diagrammet har med framgånggenererats och visat sig vara ett effektivt verktyg för studier av HEV drivlinorseffektivitet och bränsleekonomi. Dessutom visar kombinationen av detektering avkörbeteende och optimerade kontrollparametrar på en markant potentiell förbättringi bränsleförbrukning.

The automotive industry is facing some of the most difficult design challenges in industry history. Developing innovative methods to reduce fossil fuel dependence is imperative for maintaining compliance with government regulations and consumer demand. In addition to powertrain design, route selection contributes to vehicle environmental impact. The objective of this thesis is to develop a methodology for evaluating the energy consumption of each route option for a specific vehicle. A 'backwards' energy tracking method determines tractive demand at the wheels from route requirements and vehicle characteristics. Next, this method tracks energy quantities at each powertrain component. Each component model is scalable such that different vehicle powertrains may be approximated. Using an 'ecorouting' process, the most ideal route is selected by weighting relative total energy consumption and travel time. Only limited powertrain characteristics are publicly available. As the future goal of this project is to apply the model to many vehicle powertrain types, the powertrain model must be reasonably accurate with minimal vehicle powertrain characteristics. Future work expands this model to constantly re-evaluate energy consumption with real-time traffic and terrain information. While ecorouting has been applied to conventional vehicles in many publications, electrified vehicles are less studied. Hybrid vehicles are particularly complicated to model due to additional components, systems, and operation modes. This methodology has been validated to represent conventional, battery electric, and parallel hybrid electric vehicles. A sensitivity study demonstrates that the model is capable of differentiating powertrains with different parameters and routes with different characteristics. / Master of Science