Kinetic energy recovery and power management for hybrid electric vehicles

The major contribution of the work presented in this thesis is a thorough investigation of the constraints on regenerative braking and kinetic energy recovery enhancement for electric/hybrid electric vehicles during braking. Regenerative braking systems provide an opportunity to recycle the braking energy, which is otherwise dissipated as heat in the brake pads. However, braking energy harnessing is a relatively new concept in the automotive sector which still requires further research and development. Due to the operating constraints of the drivetrain architecture and the varying nature of the braking conditions, it is unlikely that all the stored kinetic energy of the vehicle can be recovered during braking.The research work in this thesis addresses the effect of braking conditions on kinetic energy recovery enhancement of the vehicle. The challenge in kinetic energy recovery enhancement lies in braking conditions, power/torque handling ability of the electric propulsion system, managing the dual braking systems, employed energy conversion techniques, and energy storage capacity. In this work a novel braking strategy is introduced to increase the involvement of the regenerative braking system, so as to increase the kinetic energy recovery while achieving the braking performance requirements. Initially mathematical modelling and simulation based analysis are presented to demonstrate the effects of braking power variation with respect to braking requirements. A novel braking strategy is proposed to increase the kinetic energy recovery during heavy braking events. The effectiveness of this braking strategy is analyzed using a simulation model developed in matlab- simulink environment. Anexperimental rig is developed to test various braking scenarios and their effects on kinetic energy recovery. A variety of braking scenarios are tested and results are presented with the analysis. At the end, suggestions are made to further continue this research in the future

Kinetic energy storage using a dual braking system for unmanned parallel hybrid electric vehicle

In this paper a novel regenerative dual braking strategy is proposed for utility/goods delivery unmanned vehicles in public roads, which improves the regenerative energy capturing ability and consequently improves the fuel use of parallel hybrid power train configurations for land unmanned vehicles where the priority is not comfort but extending the range. Furthermore, the analysis takes into account the power handling ability of the electric motor and the power converters. In previous research a plethora of regenerative braking strategies is shown, for this paper the key contribution is that the vehicle electric regeneration is related to a fixed braking distance in relation to the energy storage capabilities specifically for unmanned utility type land vehicles where passenger comfort is not a concern but pedestrian safety is of critical importance. Furthermore, the vehicle’s power converter capabilities facilitate the process of extending the braking time via introducing a variable deceleration profile. The proposed approach has therefore resulted in a regenerative algorithm which improves the vehicle’s energy storage capability without considering comfort since this analysis is applicable to unmanned vehicles. The algorithm considers the distance as the key parameter, which is associated to safety, therefore it allows the braking time period to be extended thus favouring the electric motor generation process while sustaining safety. This method allows the vehicle to brake for longer periods rather than short bursts hence resulting in a more effective regeneration with reduced use of the dual (i.e. caliper/stepper motor brake system). The regeneration method and analysis is addressed in the following paper sections. The simulation results show that the proposed regenerative braking strategy has improved significantly the energy recapturing ability of the hybrid power train configuration. The paper is also supported with experimental data that verify the theoretical development and the simulation results. The two strategies developed and implemented are Constant Braking Torque (CBT) and Constant Braking Power (CBP). Both methods were limited to a fixed safety-based distance. Overall the results demonstrate that the CBT method results in better energy-based savings

Improved winter data coverage of the Southern Ocean CO2 sink from extrapolation of summertime observations

The Southern Ocean is an important sink of anthropogenic CO2, but it is among the least well-observed ocean basins, and consequentially substantial uncertainties in the CO2 flux reconstruction exist. A recent attempt to address historically sparse wintertime sampling produced ‘pseudo’ wintertime observations of surface pCO2 using subsurface summertime observations south of the Antarctic Polar Front. Here, we present an estimate of the Southern Ocean CO2 sink that combines a machine learning-based mapping method with an updated set of pseudo observations that increases regional wintertime data coverage by 68 compared with the historical dataset. Our results confirm the suggestion that improved winter coverage has a modest impact on the reconstruction, slightly strengthening the uptake trend in the 2000s. After also adjusting for surface boundary layer temperature effects, we find a 2004-2018 mean sink of −0.16 ± 0.07 PgC yr−1 south of the Polar Front and −1.27 ± 0.23 PgC yr−1 south of 35°S, consistent with independent estimates from atmospheric data. © 2022, The Author(s)

Constraints on Asian and European sources of methane from Ch 4-C2H6-CO correlations in Asian outflow

Aircraft observations of Asian outflow from the Transport and Chemical Evolution Over the Pacific (TRACE-P) aircraft mission over the NW Pacific (March and April 2001) show large CH4 enhancements relative to background, as well as strong CH4-C2H 6-CO correlations that provide signatures of regional sources. We apply a global chemical transport model simulation of the CH4-C2H6-CO system for the TRACE-P period to interpret these observations in terms of CH4 sources and to explore in particular the unique constraints from the CH 4-C2H6-CO correlations. We use as a priori a global CH4 source inventory constrained with National Oceanic and Atmospheric Administration (NOAA) Climate Monitoring and Diagnostics Laboratory (CMDL) surface observations [Wang et al., 2004]. We find that the observed CH4 concentration enhancements and CH4-C2H6-CO correlations in Asian outflow in TRACE-P are deterinined mainly by anthropogenic emissions from China and Eurasia (defined here as Europe and eastern Russia), with only little contribution from tropical sources (wetlands and biomass burning). The a priori inventory overestimates the observed CH4 enhancements and shows regionally variable biases for the CH4/C2H6 slope. The CH 4/CO slopes are simulated without significant bias. Matching both the observed CH4 enhancements and the CH 4-C2H6-CO slopes in Asian outflow requires increasing the east Asian anthropogenic source of CH 4, and decreasing the Eurasian anthropogenic source, by at least 30% for both. The need to increase the east Asian source is driven by the underestimate of the CH4/C2H 6 slope in boundary layer Chinese outflow. The Streets et al. [2003] anthropogenic emission inventory for east Asia fits this constraint by increasing CH4 emissions from that region by 40% relative to the a priori, largely because of higher livestock and landfill source estimates. Eurasian sources (mostly European) then need to be reduced by 30-50% from the a priori value of 68 Tg yr -1. The decrease of European sources could result in part from recent mitigation of emissions from coal mining and landfills. Copyright 2004 by the American Geophysical Union

Improved quantification of Chinese carbon fluxes using CO2/CO correlations in Asian outflow

[1] We use observed CO2:CO correlations in Asian outflow from the TRACE-P aircraft campaign (February–April 2001), together with a three-dimensional global chemical transport model (GEOS-CHEM), to constrain specific components of the east Asian CO2 budget including, in particular, Chinese emissions. The CO2/CO emission ratio varies with the source of CO2 (different combustion types versus the terrestrial biosphere) and provides a characteristic signature of source regions and source type. Observed CO2/CO correlation slopes in east Asian boundary layer outflow display distinct regional signatures ranging from 10–20 mol/mol (outflow from northeast China) to 80 mol/mol (over Japan). Model simulations using best a priori estimates of regional CO2 and CO sources from Streets et al. [2003] (anthropogenic), the CASA model (biospheric), and Duncan et al. [2003] (biomass burning) overestimate CO2 concentrations and CO2/CO slopes in the boundary layer outflow. Constraints from the CO2/CO slopes indicate that this must arise from an overestimate of the modeled regional net biospheric CO2 flux. Our corrected best estimate of the net biospheric source of CO2 from China for March–April 2001 is 3200 Gg C/d, which represents a 45 % reduction of the net flux from the CASA model. Previous analyses of the TRACE-P data had found that anthropogenic Chinese C

Constraints on global oceanic emissions of N2O from observations and models

We estimate the global ocean N2O flux to the atmosphere and its confidence interval using a statistical method based on model perturbation simulations and their fit to a database of ΔpN2O (n =  6136). We evaluate two submodels of N2O production. The first submodel splits N2O production into oxic and hypoxic pathways following previous publications. The second submodel explicitly represents the redox transformations of N that lead to N2O production (nitrification and hypoxic denitrification) and N2O consumption (suboxic denitrification), and is presented here for the first time. We perturb both submodels by modifying the key parameters of the N2O cycling pathways (nitrification rates; NH4+ uptake; N2O yields under oxic, hypoxic and suboxic conditions) and determine a set of optimal model parameters by minimisation of a cost function against four databases of N cycle observations. Our estimate of the global oceanic N2O flux resulting from this cost function minimisation derived from observed and model ΔpN2O concentrations is 2.4 ± 0.8 and 2.5 ± 0.8 Tg N yr−1 for the two N2O submodels. These estimates suggest that the currently available observational data of surface ΔpN2O constrain the global N2O flux to a narrower range relative to the large range of results presented in the latest IPCC report

Towards understanding the variability in biospheric CO2 fluxes:Using FTIR spectrometry and a chemical transport model to investigate the sources and sinks of carbonyl sulfide and its link to CO2

Understanding carbon dioxide (CO2) biospheric processes is of great importance because the terrestrial exchange drives the seasonal and interannual variability of CO2 in the atmosphere. Atmospheric inversions based on CO2 concentration measurements alone can only determine net biosphere fluxes, but not differentiate between photosynthesis (uptake) and respiration (production). Carbonyl sulfide (OCS) could provide an important additional constraint: it is also taken up by plants during photosynthesis but not emitted during respiration, and therefore is a potential means to differentiate between these processes. Solar absorption Fourier Transform InfraRed (FTIR) spectrometry allows for the retrievals of the atmospheric concentrations of both CO2 and OCS from measured solar absorption spectra. Here, we investigate co-located and quasi-simultaneous FTIR measurements of OCS and CO2 performed at five selected sites located in the Northern Hemisphere. These measurements are compared to simulations of OCS and CO2 using a chemical transport model (GEOS-Chem). The coupled biospheric fluxes of OCS and CO2 from the simple biosphere model (SiB) are used in the study. The CO2 simulation with SiB fluxes agrees with the measurements well, while the OCS simulation reproduced a weaker drawdown than FTIR measurements at selected sites, and a smaller latitudinal gradient in the Northern Hemisphere during growing season when comparing with HIPPO (HIAPER Pole-to-Pole Observations) data spanning both hemispheres. An offset in the timing of the seasonal cycle minimum between SiB simulation and measurements is also seen. Using OCS as a photosynthesis proxy can help to understand how the biospheric processes are reproduced in models and to further understand the carbon cycle in the real world

Precision Requirements for Space-based XCO2 Data

Precision requirements have been determined for the column-averaged CO2 dry air mole fraction (X(sub CO2)) data products to be delivered by the Orbiting Carbon Observatory (OCO). These requirements result from an assessment of the amplitude and spatial gradients in X(sub CO2), the relationship between X(sub CO2) precision and surface CO2 flux uncertainties calculated from inversions of the X(sub CO2) data, and the effects of X,,Z biases on CO2 flux inversions. Observing system simulation experiments and synthesis inversion modeling demonstrate that the OCO mission design and sampling strategy provide the means to achieve the X(sub CO2) precision requirements. The impact of X(sub CO2) biases on CO2 flux uncertainties depend on their spatial and temporal extent since CO2 sources and sinks are inferred from regional-scale X(sub CO2) gradients. Simulated OCO sampling of the TRACE-P CO2 fields shows the ability of X(sub CO2) data to constrain CO2 flux inversions over Asia and distinguish regional fluxes from India and China

Error Correlation Between CO2 and CO as Constraint for CO2 Flux Inversions Using Satellite Data

Inverse modeling of CO2 satellite observations to better quantify carbon surface fluxes requires a chemical transport model (CTM) to relate the fluxes to the observed column concentrations. CTM transport error is a major source of uncertainty. We show that its effect can be reduced by using CO satellite observations as additional constraint in a joint CO2-CO inversion. CO is measured from space with high precision, is strongly correlated with CO2, and is more sensitive than CO2 to CTM transport errors on synoptic and smaller scales. Exploiting this constraint requires statistics for the CTM transport error correlation between CO2 and CO, which is significantly different from the correlation between the concentrations themselves. We estimate the error correlation globally and for different seasons by a paired-model method (comparing GEOS-Chem CTM simulations of CO2 and CO columns using different assimilated meteorological data sets for the same meteorological year) and a paired-forecast method (comparing 48- vs. 24-h GEOS-5 CTM forecasts of CO2 and CO columns for the same forecast time). We find strong error correlations (r2>0.5) between CO2 and CO columns over much of the extra-tropical Northern Hemisphere throughout the year, and strong consistency between different methods to estimate the error correlation. Application of the averaging kernels used in the retrieval for thermal IR CO measurements weakens the correlation coefficients by 15% on average (mostly due to variability in the averaging kernels) but preserves the large-scale correlation structure. We present a simple inverse modeling application to demonstrate that CO2-CO error correlations can indeed significantly reduce uncertainty on surface carbon fluxes in a joint CO2-CO inversion vs. a CO2-only inversion.Earth and Planetary SciencesEngineering and Applied Science

Variability of North Atlantic CO2 fluxes for the 2000-2017 period estimated from atmospheric inverse analyses

This is the final version. Available on open access from the European Geosciences Union via the DOI in this recordData availability: The data sources are the following: (i) Atmospheric CO2 measurements were taken from obspack_co2_1_GLOBALVIEWplus_v4.2_2019-03-19 (https://gml.noaa.gov/ccgg/obspack/data.php?id=obspack_co2_1_GLOBALVIEWplus_v4.2_2019-03-19, (ObsPack, Cooperative Global Atmospheric Data Integration Project, 2018, last access: 14 October 2020); (ii) Prior ocean flux oc_v1.7 from Rödenbeck et al. (2013) were taken from http://www.bgc-jena.mpg.de/CarboScope/ (last access: 5 June 2020). Prior ocean flux from Landschützer et al. (2016) were taken from https://www.ncei.noaa.gov/access/ocean-carbon-data-system/oceans/SPCO2_1982_present_ETH_SOM_FFN.html (last access: 6 May 2020). Prior ocean flux from Takahashi et al. (2009) were taken from ftp://ftp.as.harvard.edu/gcgrid/geos-chem (last access: 9 July 2018). (iii) CarbonTracker CT2019 results were provided by NOAA ESRL, Boulder, Colorado, USA, from the website at http://carbontracker.noaa.gov (Jacobson et al., 2020, last access: 15 May 2020). CTE flux estimates were downloaded from ftp://ftp.wur.nl/carbontracker/data/fluxes/data_flux1x1_monthly/ (van der Laan-Luijkx et al., 2017, last access: 24 November 2020). The flux estimates from CAMS (v18r2) were taken from https://apps.ecmwf.int/datasets/data/cams-ghg-inversions/ (Chevallier et al., 2019, last access: 6 December 2019). (iv) The model CO2 fluxes for JULES (land) and GOBMs (ocean) were taken from Le Quéré et al. (2018). Time series of reconstructed surface ocean pCO2 and CO2 fluxes (LSCE-FFNN) from Denvil-Sommer et al. (2019) are the first version of CMEMS, downloaded from https://resources.marine.copernicus.eu/?option=com_csw&task=results (last access: 14 January 2021). The products from Iida et al. (2015) were downloaded from http://www.data.jma.go.jp/gmd/kaiyou/english/co2_flux/co2_flux_data_en.html (last access: 14 January 2021). The products from Zeng et al. (2015) were downloaded from https://db.cger.nies.go.jp/DL/10.17595/20201020.001.html.en (last access: 14 January 2021). The products from CMEMS, CSIR, and Watson were taken from Friedlingstein et al. (2020).We present new estimates of the regional North Atlantic (15–80∘ N) CO2 flux for the 2000–2017 period using atmospheric CO2 measurements from the NOAA long-term surface site network in combination with an atmospheric carbon cycle data assimilation system (GEOS-Chem–LETKF, Local Ensemble Transform Kalman Filter). We assess the sensitivity of flux estimates to alternative ocean CO2 prior flux distributions and to the specification of uncertainties associated with ocean fluxes. We present a new scheme to characterize uncertainty in ocean prior fluxes, derived from a set of eight surface pCO2-based ocean flux products, and which reflects uncertainties associated with measurement density and pCO2-interpolation methods. This scheme provides improved model performance in comparison to fixed prior uncertainty schemes, based on metrics of model–observation differences at the network of surface sites. Long-term average posterior flux estimates for the 2000–2017 period from our GEOS-Chem–LETKF analyses are −0.255 ± 0.037 PgC yr−1 for the subtropical basin (15–50∘ N) and −0.203 ± 0.037 PgC yr−1 for the subpolar region (50–80∘ N, eastern boundary at 20∘ E). Our basin-scale estimates of interannual variability (IAV) are 0.036 ± 0.006 and 0.034 ± 0.009 PgC yr−1 for subtropical and subpolar regions, respectively. We find statistically significant trends in carbon uptake for the subtropical and subpolar North Atlantic of −0.064 ± 0.007 and −0.063 ± 0.008 PgC yr−1 decade−1; these trends are of comparable magnitude to estimates from surface ocean pCO2-based flux products, but they are larger, by a factor of 3–4, than trends estimated from global ocean biogeochemistry models.Natural Environment Research Council (NERC