Patrik Soltic

Optimal Hybridization in Two Parallel Hybrid Electric Vehicles using Dynamic Programming

Abstract This study explores different hybridization ratios of two types of parallel hybrid electric vehicles, a torque assist parallel hybrid and a full parallel hybrid, with equal power-to-weight ratio. The powertrain consist of an internal combustion engine, an electric motor, and a NiMH battery. The different hybridization ratios are compared by their optimal fuel consumption for eight different drive cycles. The optimal fuel consumption is determined using dynamic programming for each of the different hybridization ratios. In the full parallel hybrid the engine and motor can be decoupled while in the torque assist hybrid the engine and motor are always mechanically connected. Results show that there are not only lower fuel consumption for the full hybrid but the need for hybridization is lower than in the torque assist hybrid for all eight cycles. The hybridization ratio where a full hybrid have the same fuel consumption as the optimal torque assist hybrid can differ as much as 51%.

Torque-Assist Hybrid Electric Powertrain Sizing: From Optimal Control Towards a Sizing Law

In this study a novel method is proposed with which the optimal hybridization ratio of a torque-assist hybrid electric powertrain can be found with very little computational effort. The objective is to minimize the total CO2 emissions of the vehicle, while maintaining its drivability at a constant level. The starting point is an analysis in which the optimal driving strategy is found for eight typical driving cycles using dynamic programming. Analyzing these results, a simple yet powerful rule-based method is proposed that allows to choose the sizes of the combustion engine and of the electric motor such that the CO2 emissions are very close to the minimum value, i.e., with a deviation of less than 1% for most driving cycles.

A Transmission-Actuated Energy-Management Strategy

In this paper, we analyze a hybrid electric vehicle structure and propose a simple and computationally cheap yet close-to-optimal energy-management strategy. The underlying hybrid configuration is of parallel type. Furthermore, the parallel hybrid does not include a clutch between the electric motor and the engine. The considered vehicle uses a six-speed dual-clutch transmission (DCT). The proposed supervisory controller considers both the torque split management and the gear-shifting strategy. Results show that the proposed approach achieves fuel consumption (FC) within 1% of the global optimum for most driving cycles. In addition, using the proposed controller, the number of gears in the gearbox can be reduced to three while maintaining the FC within 2% of what is achieved with a six-speed gearbox. Moreover, the results shown in this paper are not sensitive to limitations and energy losses associated with gear shifting.

Combustion Characteristics of Hydrogen-Natural Gas Mixtures in Passenger Car Engines

The presented concept in this study consists of a state-of-the-art passenger car natural gas engine fired by different hydrogen (H\d2) and compressed-natural-gas (CNG) fuel blends. The hydrogen content in the fuel was varied among 5 and 15 vol% corresponding to 0.6-2.1 mass%, while comparisons include also engine operation on pure CNG. Increasing hydrogen content of the fuel accelerated combustion leading to modest efficiency improvements. Combustion analysis showed that the increasing burning rates mainly affected the initial combustion phase (duration for 5% mass fraction burned). With optimal combinations of spark timing and EGR rate the achievements are additional efficiency increase with substantially lower engine-out NO\dx while total unburned hydrocarbons or CO-engine-out emissions are not affected. Investigations using Design of Experiments (DoE) algorithms provided a comprehensive picture of the entire parameter space. The investigations showed two fuel consumption optimal combustion domains: Low EGR and late spark timing with associated high engine-out NO\dx emissions as well as high EGR and early spark timing with very low engine-out NO\dx.

Simultaneous measurement of NO and NO(2) by dual-wavelength quantum cascade laser spectroscopy.

The concept of a multi-wavelength quantum cascade laser emitting at two or more spectrally well-separated wavelengths is highly appealing for applied spectroscopy, as it allows detecting several species with compact and cost-efficient optical setups. Here we present a practical realization of such a dual-wavelength setup, which is based on a room-temperature quantum cascade laser emitting single-mode at 1600 cm-1 and 1900 cm-1 and is thus well-suited for simultaneous NO and NO2 detection. Operated in a time-division multiplexed mode, our spectrometer reaches detection limits of 0.5 and 1.5 ppb for NO2 and NO, respectively. The performance of the system is validated against the well-established chemiluminescence detection while measuring the NOx emissions on an automotive test-bench, as well as upon monitoring the pollution at a suburban site.

The cold start emissions of light-duty-vehicle fleets: A simplified physics-based model for the estimation of CO2 and pollutants

The emissions from hot driving conditions, in which the exhaust-after-treatment systems are working properly, continue to decrease, which is why the emissions of cold starts have gained in importance. Traffic emission models are used to estimate and predict vehicle fleet emissions and the air quality of countries, regions, cities, etc. In addition to the statistical input of fleet activities, these models are mostly based on the use of separate emission sub-models for hot driving and cold start driving. In reality, the cold start models are almost entirely empirical and of limited accuracy. In this work, a model is developed that is based on physical reasoning, i.e., it is based on energy balances. Because many details, such as the thermal conductivities and the engine control decisions, are unknown, the model must be able to address different simplifications. The model can be parameterized with as few as two tests per vehicle. It is applied to several car samples (six to eight vehicles each) of different technical generations and shows reliable prediction for any combination of the driving pattern (including gradient), the ambient temperature, the stop time before the ride and the duration of the ride (if shorter than the warm-up phase).

Performance simulations of engine-gearbox combinations for lightweight passenger cars

Abstract This paper compares the fuel consumption of lightweight passenger cars with three different types of engine (one low speed and one high speed naturally aspirated spark ignited, one turbo-charged compression ignited) and two different types of transmission [continuously variable transmission (CVT) and automated gear drive]. All fuel consumption results are obtained using a quasi-static driving cycle simulator. The implemented models are described in detail. The engines are represented through their eficiency maps, which are obtained by scaling published data. Effciency of the transmission (CVT or gear drive) is modelled in dependence on speed, torque and gear ratio. The simulations show that low fuel consumption can be achieved with all those concepts. CVTs show similar results to automated gear drives. The CVTs theoretical advantage of operating the engine at its most fuel-efficient points is compensated by the relatively low efficiency.

Real-world and type-approval emission evolution of passenger cars

The investigation of several passenger car generations with gasoline engines shows that the emissions depend very strongly on the driving cycle. Official type approval cycles allow just very inaccurate predications about their real-world emissions. The measured gasoline vehicles have up to factor 11 higher real-life emissions than in type approval cycles. However, a clear reduction of real-world emissions can be seen over the different investigated generations of gasoline cars. In addition, it can be seen that the cold start emissions depend strongly on ambient temperature levels for all generations of cars and that the cold start accounts for an increasing part of the total pollutant emissions. As an extreme example, the cold start hydrocarbon emissions of Euro-3 cars at -20°C ambient temperature correspond approximately to those of 1,000 km driving with warm engines.

Performance evaluation of gasoline alternatives using a thermodynamic spark-ignition engine model

In light of climate change and due to the fact that surface transportation heavily relies on internal combustion engines, many different alternatives to gasoline have been proposed. Herein, we present a model, incorporating only first order effects, which allows a quick assessment of the suitability of a certain molecule as a replacement for gasoline. Using global sensitivity analysis, the elemental composition and the vapor heat capacity have been identified as main influencing fuel parameters. A case study using the currently proposed alternative fuels (methanol, ethanol, n-butanol, dimethylfuran, methylfuran, and α-pinene) as well as gasoline and several hydrocarbons (cyclohexane, n-heptane, isooctane, and benzene) revealed n-butanol as the best performing alternative fuel. The use of this compound entails a significant decrease in CO2 emissions and an increased efficiency, but also a higher consumption in comparison with gasoline.

Multi-color laser spectroscopy with a dual-wavelength quantum cascade laser

A new concept of multi-color spectroscopy based on a dual-wavelength QCL is presented. The latter emits at two distinct wavelengths (5.26 and 6.25 μm), featuring simultaneous detection of two different gas species without any beam combining optics.