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Current research has led to a significant improvement at the system level of thermoelectric generators (TEG) for automotive applications. The previously low power density could be increased considerably up to 267 W/kg and 478 W/dm3. In addition, the cost–benefit ratio of the technology in the overall system of the vehicle was improved through intensive optimizations on system level. The results presented so far are based on measurement data of single thermoelectric modules (TEM) and simulation of the TEG system. In this paper the high simulative increases at the system level, achieved through a holistic optimization method, are validated by a functional prototype, completely equipped with TEM. Thereby, a functional prototype has been developed and built successfully and measured on a hot gas test bench. In the experiment all TEM show a stable power output and the highest gravimetric power density of automotive TEG systems known to the authors could be measured. Further tests will be performed with the functional prototype as described in the outlook. In addition to the successful tests, the simulation is validated with the detailed measurement data. After adapting the measurement method of the TEM for providing more accurate TEM measurement data as input for the simulation, a suitable match could be achieved between the TEG simulation and the experiment. In the measurement points performed so far, the accuracy of the simulated temperatures reaches more than 95%. The accuracy of the simulated output power is more than 97%. [ABSTRACT FROM AUTHOR]

One of the major challenges of the future automotive development is to achieve the required reductions of the CO2 emissions. Therefore, it is necessary to investigate all potential technologies for efficiency improvement. In a combustion engine, about 2/3 of the chemical energy of the fuel is dissipated as waste heat. Due to its high temperature level, the waste heat in the exhaust gas is very promising for the technology of thermoelectric generators (TEG). In this work the methodology for a holistic TEG optimization for automotive vehicle applications will be presented. Thereby, all system interactions between the vehicle and the TEG are modelled and the CO2 reduction can be optimized within the vehicle system. Moreover the costs are calculated for each TEG design, and the method realizes an optimization of the cost–benefit ratio in a direct way. The optimization method is applied with a highly integrated TEG design, which has been developed to be compact and lightweight. Through the combination of improvements in TEG design and system optimization, a gravimetric power density of 267 W/kg and a volumetric power density of 478 W/dm^3 could be achieved. These power densities are about 900% and 700%, respectively, higher than the state of the art. The optimization method was applied exemplarily to a conventional vehicle (Volkswagen Golf VII) and a hybrid vehicle (Opel Ampera/Chevrolet Volt). As a result, reductions in consumption and CO2 emissions of up to 2.2% for the conventional and 3.4% for the hybrid vehicle could be achieved within the worldwide harmonized light duty driving test cycle. The cost–benefit optimum is 81.3 €/(g/km) for the conventional vehicle and 54.8 €/(g/km) for the hybrid vehicle in charge sustaining mode. [ABSTRACT FROM AUTHOR]

Waste heat recovery, using thermoelectric power technology, is a promising approach to reduce fuel consumption and CO2 emissions on passenger cars. However, possible application requires optimizing heat exchangers and defining adequate thermoelectric materials to improve efficiency. A dynamic model has been developed to investigate the application of a thermoelectric generator (TEG) for waste heat recovery in an automotive engine exhaust. The converted electrical energy is used to charge a 12 V battery. The model evaluates the amount of recovered energy over a prescribed drive-cycle. It also evaluates the effect of system integration on the TEG performances, such as fuel consumption, temperatures downstream of the TEG and the relative counter pressure. Experiments are done on both a thermoelectric module (TEM) test rig and a diesel engine test rig equipped with a TEG prototype. Simulations of steady operating points show good agreement with experimental data. The results show a maximum power of 42 W generated by the TEG, with a maximum power of 1.5 W per module (corresponding to TEM hot side temperature of 671 K and TEM cold side temperature of 354 K). At the end of the duty cycle, the energy recovered by the vehicle battery is around 27 kJ (7.5 Wh). The engine counter pressure exceeds 30 mbar when the mass flow rate is higher than 36 g s−1. The simulation results of temperatures, pressures, and output power show that the model can be used as a basis to develop a TEG with high performance that ensure safety operation of the engine and the after treatment system. [ABSTRACT FROM AUTHOR]

This paper deals with double saliency switched reluctance motor for automotive application by offering simultaneously a design solution to the drawbacks of torque ripples and emitted noise caused by the important radial efforts. The work concerns the optimization of the motor structure, the main objectives is the reduction of the first harmonics of torque and radial force applied on the stator teeth. This geometric optimization is performed on operating points where the instantaneous computation of supply current is taken into account to resolve simultaneously both problems. This operating point is defined as torque–speed point by considering the instantaneous characteristics of the machine when the steady state is established. [ABSTRACT FROM AUTHOR]

Maximizing electrical energy generation through waste heat recovery is one of the modern research questions within automotive applications of thermoelectric (TE) technologies. This paper proposes a novel concept of distributed multisection multilevel DC-DC conversion networks based on thermoelectric generators (TEGs) for automotive applications. The concept incorporates a bottom-up design approach to collect, convert, and manage vehicle waste heat efficiently. Several state-of-the-art thermoelectric materials are analyzed for the purpose of power generation at each waste heat harvesting location on a vehicle. Optimal materials and TE couple configurations are suggested. Moreover, a comparison of prevailing DC-DC conversion techniques was made with respect to applications at each conversion level within the network. Furthermore, higher-level design considerations are discussed according to system specifications. Finally, a case study is performed to compare the performance of the proposed network and a traditional single-stage system. The results show that the proposed network enhances the system conversion efficiency by up to 400%. [ABSTRACT FROM AUTHOR]

The power output of a thermoelectric generator (TEG) was investigated under engine partial-load operation based on measured exhaust gas temperatures and mass flow rates. Materials with properties required for highend temperature TE couples (>500°C) were evaluated. Various possible material combinations for p- and n-legs of these couples as well as the conflicting targets of high efficiency and low cost as required for automotive mass production are discussed. New skutterudite materials for both p- and n-legs as identified during a joint research project are presented, which can help to overcome this conflict. Efficiencies >10% were achieved with these new materials, which have potentially twofold lower production costs than telluride-based materials due to the price of their elements. Some potential for improvement in efficiency and costs has been identified by developing highly integrated TEG units, specifically designed for automotive applications. These initial results of the material development and the evaluation of different integration concepts will be applied in a subsequent step for the fabrication of a pilot number of TEG modules/units. [ABSTRACT FROM AUTHOR]

The paper deals with a diagnostic method that allows to detect engineknock. The developed algorithm differentiates three kinds of engine cycles:absence of knock, increasing knock and heavy knock. The decision is takenfrom a block vibration signal. The diagnostic method is based on patternrecognition. Three models of different data shapes provided from theaccelerometer are elaborated. This is done using a time-scale analysis toolcalled a wavelet network. It allows to extract relevant features from thesignal. The aim of the method is then to partition the feature space intoclasses representing the knock states. Experimental results are reported. [ABSTRACT FROM AUTHOR]