Achieving Synergistic Improvement in Dielectric and Energy Storage Properties of All-Organic Poly(Methyl Methacrylate)-Based Copolymers Via Establishing Charge Traps

How to achieve synergistic improvement of permittivity(ε_(r))and breakdown strength(E_(b))is a huge challenge for polymer dielectrics.Here,for the first time,theπ-conjugated comonomer(MHT)can simultaneously promote theε_(r)and E_(b)of linear poly(methyl methacrylate)(PMMA)copolymers.The PMMA-based random copolymer films(P(MMA-co-MHT)),block copolymer films(PMMA-b-PMHT),and PMMA-based blend films were prepared to investigate the effects of sequential structure,phase separation structure,and modification method on dielectric and energy storage properties of PMMA-based dielectric films.As a result,the random copolymer P(MMA-coMHT)can achieve a maximumε_(r)of 5.8 at 1 kHz owing to the enhanced orientation polarization and electron polarization.Because electron injection and charge transfer are limited by the strong electrostatic attraction ofπ-conjugated benzophenanthrene group analyzed by the density functional theory(DFT),the discharge energy density value of P(MMA-co-PMHT)containing 1 mol%MHT units with the efficiency of 80%reaches15.00 J cm^(-3)at 872 MV m^(-1),which is 165%higher than that of pure PMMA.This study provides a simple and effective way to fabricate the high performance of polymer dielectrics via copolymerization with the monomer of P-type semi-conductive polymer.

Inter-stage performance and energy characteristics analysis of electric submersible pump based on entropy production theory

The electric submersible pump(ESP) is a crucial apparatus utilized for lifting in the oil extraction process.Its lifting capacity is enhanced by the multi-stage tandem structure, but variations in energy characteristics and internal flow across stages are also introduced. In this study, the inter-stage variability of energy characteristics in ESP hydraulic systems is investigated through entropy production(EP) analysis,which incorporates numerical simulations and experimental validation. The EP theory facilitates the quantification of energy loss in each computational subdomain at all ESP stages, establishing a correlation between microscopic flow structure and energy dissipation within the system. Furthermore, the underlying causes of inter-stage variability in ESP hydraulic systems are examined, and the advantages and disadvantages of applying the EP theory in this context are evaluated. Consistent energy characteristics within the ESP, aligned with the distribution of internal flow structure, are provided by the EP theory, as demonstrated by our results. The EP theory also enables the quantitative analysis of internal flow losses and complements existing performance analysis methods to map the internal flow structure to hydraulic losses. Nonetheless, an inconsistency between the energy characterization based on EP theory and the traditional efficiency index when reflecting inter-stage differences is identified. This inconsistency arises from the exclusive focus of the EP theory on flow losses within the flow field, disregarding the quantification of external energy input to the flow field. This study provides a reference for the optimization of EP theory in rotating machinery while deeply investigating the energy dissipation characteristics of multistage hydraulic system, which has certain theoretical and practical significance.

Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network optimization.This study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic RESs.The primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss mitigation.Additionally,a carbon tax is included in the objective function to reduce carbon emissions.Thorough scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal solutions.Simulation results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution quality.Notably,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)effectively.This research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local minima.GBBLCO emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

Energy Storage Operation Modes in Typical Electricity Market and Their Implications for China

As the Chinese government proposes ambitious plans to promote low-carbon transition,energy storage will play a pivotal role in China’s future power system.However,due to the lack of a mature electricity market environment and corresponding mechanisms,current energy storage in China faces problems such as unclear operational models,insufficient cost recovery mechanisms,and a single investment entity,making it difficult to support the rapid development of the energy storage industry.In contrast,European and American countries have already embarked on certain practices in energy storage operation models.Through exploration of key issues such as investment entities,market participation forms,and cost recovery channels in both front and back markets,a wealth of mature experiences has been accumulated.Therefore,this paper first summarizes the existing practices of energy storage operation models in North America,Europe,and Australia’s electricity markets separately from front and back markets,finding that perfect market mechanisms and reasonable subsidy policies are among the main drivers for promoting the rapid development of energy storage markets.Subsequently,combined with the actual development of China’s electricity market,it explores three key issues affecting the construction of costsharing mechanisms for energy storage under market conditions:Market participation forms,investment and operation modes,and cost recovery mechanisms.Finally,in line with the development expectations of China’s future electricitymarket,suggestions are proposed fromfour aspects:Market environment construction,electricity price formation mechanism,cost sharing path,and policy subsidy mechanism,to promote the healthy and rapid development of China’s energy storage industry.

Enhanced Deep Reinforcement Learning Strategy for Energy Management in Plug-in Hybrid Electric Vehicles with Entropy Regularization and Prioritized Experience Replay

Plug-in Hybrid Electric Vehicles(PHEVs)represent an innovative breed of transportation,harnessing diverse power sources for enhanced performance.Energy management strategies(EMSs)that coordinate and control different energy sources is a critical component of PHEV control technology,directly impacting overall vehicle performance.This study proposes an improved deep reinforcement learning(DRL)-based EMSthat optimizes realtime energy allocation and coordinates the operation of multiple power sources.Conventional DRL algorithms struggle to effectively explore all possible state-action combinations within high-dimensional state and action spaces.They often fail to strike an optimal balance between exploration and exploitation,and their assumption of a static environment limits their ability to adapt to changing conditions.Moreover,these algorithms suffer from low sample efficiency.Collectively,these factors contribute to convergence difficulties,low learning efficiency,and instability.To address these challenges,the Deep Deterministic Policy Gradient(DDPG)algorithm is enhanced using entropy regularization and a summation tree-based Prioritized Experience Replay(PER)method,aiming to improve exploration performance and learning efficiency from experience samples.Additionally,the correspondingMarkovDecision Process(MDP)is established.Finally,an EMSbased on the improvedDRLmodel is presented.Comparative simulation experiments are conducted against rule-based,optimization-based,andDRL-based EMSs.The proposed strategy exhibitsminimal deviation fromthe optimal solution obtained by the dynamic programming(DP)strategy that requires global information.In the typical driving scenarios based onWorld Light Vehicle Test Cycle(WLTC)and New European Driving Cycle(NEDC),the proposed method achieved a fuel consumption of 2698.65 g and an Equivalent Fuel Consumption(EFC)of 2696.77 g.Compared to the DP strategy baseline,the proposed method improved the fuel efficiency variances(FEV)by 18.13%,15.1%,and 8.37%over the Deep QNetwork(DQN),Double DRL(DDRL),and original DDPG methods,respectively.The observational outcomes demonstrate that the proposed EMS based on improved DRL framework possesses good real-time performance,stability,and reliability,effectively optimizing vehicle economy and fuel consumption.

Electricity as an Energy Vector: A Performance Comparison with Hydrogen and Biodiesel in Italy

This study presents a comparative analysis of electricity, hydrogen, and biodiesel as energy vectors, with a focus on powering an aluminum smelter in southern Italy. It evaluates these vectors in terms of efficiency, land requirements for carbon-neutral energy production, and capital expenditure, providing insights throughout the entire supply chain (upstream, midstream, and downstream) into their feasibility for industrial applications. The research reveals that biodiesel, despite being carbon neutral, is impractical due to extensive land requirements and lower efficiency if compared to other vectors. Hydrogen, downstream explored in two forms as thermal power generation and fuel cell technology, shows lower efficiency and higher capital expenditure compared to electricity. Additionally, green hydrogen production’s land requirements significantly exceed those of electricity-based systems. Electricity emerges as the most viable option, offering an overall higher efficiency, lower land requirements for its green production, and comparatively lower capital expenditure. The study’s findings highlight the importance of a holistic assessment of energy vectors, considering economic, environmental, and practical aspects along the entire energy supply chain, especially in industrial applications where the balance of these factors is crucial for long-term sustainability and feasibility. This comprehensive analysis provides valuable guidance for similar industrial applications, emphasizing the need for a balanced approach in the selection of energy vectors.

Electrical characteristics of new three-phase traction power supply system for rail transit

A novel three-phase traction power supply system is proposed to eliminate the adverse effects caused by electric phase separation in catenary and accomplish a unifying manner of traction power supply for rail transit.With the application of two-stage three-phase continuous power supply structure,the electrical characteristics exhibit new features differing from the existing traction system.In this work,the principle for voltage levels determining two-stage network is dissected in accordance with the requirements of traction network and electric locomotive.The equivalent model of three-phase traction system is built for deducing the formula of current distribution and voltage losses.Based on the chain network model of the traction network,a simulation model is established to analyze the electrical characteristics such as traction current distribution,voltage losses,system equivalent impedance,voltage distribution,voltage unbalance and regenerative energy utilization.In a few words,quite a lot traction current of about 99%is undertaken by long-section cable network.The proportion of system voltage losses is small attributed to the two-stage three-phase power supply structure,and the voltage unbal-ance caused by impedance asymmetry of traction network is less than 1‰.In addition,the utilization rate of regenerative energy for locomotive achieves a significant promotion of over 97%.

Power-balancing Instantaneous Optimization Energy Management for a Novel Series-parallel Hybrid Electric Bus

Energy management（EM） is a core technique of hybrid electric bus（HEB） in order to advance fuel economy performance optimization and is unique for the corresponding configuration. There are existing algorithms of control strategy seldom take battery power management into account with international combustion engine power management. In this paper, a type of power-balancing instantaneous optimization（PBIO） energy management control strategy is proposed for a novel series-parallel hybrid electric bus. According to the characteristic of the novel series-parallel architecture, the switching boundary condition between series and parallel mode as well as the control rules of the power-balancing strategy are developed. The equivalent fuel model of battery is implemented and combined with the fuel of engine to constitute the objective function which is to minimize the fuel consumption at each sampled time and to coordinate the power distribution in real-time between the engine and battery. To validate the proposed strategy effective and reasonable, a forward model is built based on Matlab/Simulink for the simulation and the dSPACE autobox is applied to act as a controller for hardware in-the-loop integrated with bench test. Both the results of simulation and hardware-in-the-loop demonstrate that the proposed strategy not only enable to sustain the battery SOC within its operational range and keep the engine operation point locating the peak efficiency region, but also the fuel economy of series-parallel hybrid electric bus（SPHEB） dramatically advanced up to 30.73% via comparing with the prototype bus and a similar improvement for PBIO strategy relative to rule-based strategy, the reduction of fuel consumption is up to 12.38%. The proposed research ensures the algorithm of PBIO is real-time applicability, improves the efficiency of SPHEB system, as well as suite to complicated configuration perfectly.

An optimal energy management development for various configuration of plug-in and hybrid electric vehicle

Due to soaring fuel prices and environmental concerns, hybrid electric vehicle(HEV) technology attracts more attentions in last decade. Energy management system, configuration of HEV and traffic conditions are the main factors which affect HEV's fuel consumption, emission and performance. Therefore, optimal management of the energy components is a key element for the success of a HEV. An optimal energy management system is developed for HEV based on genetic algorithm. Then, different powertrain system component combinations effects are investigated in various driving cycles. HEV simulation results are compared for default rule-based, fuzzy and GA-fuzzy controllers by using ADVISOR. The results indicate the effectiveness of proposed optimal controller over real world driving cycles. Also, an optimal powertrain configuration to improve fuel consumption and emission efficiency is proposed for each driving condition. Finally, the effects of batteries in initial state of charge and hybridization factor are investigated on HEV performance to evaluate fuel consumption and emissions. Fuel consumption average reduction of about 14% is obtained for optimal configuration data in contrast to default configuration. Also results indicate that proposed controller has reduced emission of about 10% in various traffic conditions.

Battery Technologies for Grid-Level Large-Scale Electrical Energy Storage

Grid-level large-scale electrical energy storage(GLEES) is an essential approach for balancing the supply–demand of electricity generation, distribution, and usage. Compared with conventional energy storage methods, battery technologies are desirable energy storage devices for GLEES due to their easy modularization, rapid response, flexible installation, and short construction cycles. In general, battery energy storage technologies are expected to meet the requirements of GLEES such as peak shaving and load leveling, voltage and frequency regulation, and emergency response, which are highlighted in this perspective. Furthermore, several types of battery technologies, including lead–acid, nickel–cadmium, nickel–metal hydride, sodium–sulfur, lithium-ion, and flow batteries, are discussed in detail for the application of GLEES. Moreover, some possible developing directions to facilitate efforts in this area are presented to establish a perspective on battery technology, provide a road map for guiding future studies, and promote the commercial application of batteries for GLEES.

Electric ignition energy evaluation and the energy distribution structure of energy released in electrostatic discharge process

Ignition energy is one of tbe important parameters of flammable materials, and evaluating ignition energy precisely is essential to the safety of process industry and combustion science and technology. By using electric spark discharge test system, a series of electric spark discharge experiments were conducted with the capacitor-stored energy in the range of 10 J, 100 J, and 1000 J, respectively. The evaluation method for energy consumed by electric spark, wire, and switch during capacitor discharge process has been studied respectively. The resistance of wire, switch, and plasma between electrodes has been evaluated by different methods and an optimized evaluation method has been obtained. The electric energy consumed by wire, electric switch, and electric spark-induced plasma between electrodes were obtained and the energy structure of capacitor-released energy was analyzed. The dynamic process and the characteristic parameters （the maximum power, duration of discharge process） of electric spark discharge process have been analyzed. Experimental results showed that, electric spark-consumed energy only accounts for 8%-14% of the capacitor-released energy. With the increase of capacitor-released energy, the duration of discharge process becomes longer, and the energy of plasma accounts for more in the capacitor-released energy. The power of electric spark varies with time as a damped sinusoids function and the period and the maximum value increase with the capacitor-released energy.

ENERGY MANAGEMENT STRATEGY FOR PARALLEL HYBRID ELECTRIC VEHICLES

Energy management strategy (EMS) is the core of the real-time controlalgorithm of the hybrid electric vehicle (HEV). A novel EMS using the logic threshold approach withincorporation of a stand-by optimization algorithm is proposed. The aim of it is to minimize theengine fuel consumption and maintain the battery state of charge (SOC) in its operation range, whilesatisfying the vehicle performance and drivability requirements. The hybrid powertrain bench testis carried out to collect data of the engine, motor and battery pack, which are used in the EMS tocontrol the powertrain. Computer simulation model of the HEV is established in the MATLAB/Simulinkenvironment according to the bench test results. Simulation results are presented for behaviors ofthe engine, motor and battery. The proposed EMS is implemented for a real parallel hybrid carcontrol system and validated by vehicle field tests.

Distribution of Electrical Field Energy for Conversion of Methane to C_2 Hydrocarbons via Dissymmetrical Electric Field Enhanced Plasma

Direct conversion of methane into C2 hydrocarbons through alternating current electric field enhanced plasma was studied under room temperature, atmospheric pressure and low power conditions. The distribution of electrical field intensity and distribution of energy were calculated with software that was developed by us according to the charge simulation method. The results indicated that the energy of tip of electrode was 0.36 J/mm^3 and it was higher than the methane dissociation energy （0.0553 J/mm^3）. The methane located at this area can be activated easily. The higher-energy particles produced by dissociation collided with molecules around them and initiated consecutive reactions between free radicals and molecules. The method was proved to be valided and could be taken as a basis for the electrical field study concerned.

Energy-Optimal Braking Control Using a Double-Layer Scheme for Trajectory Planning and Tracking of Connected Electric Vehicles

Most researches focus on the regenerative braking system design in vehicle components control and braking torque distribution,few combine the connected vehicle technologies into braking velocity planning.If the braking intention is accessed by the vehicle-to-everything communication,the electric vehicles(EVs)could plan the braking velocity for recovering more vehicle kinetic energy.Therefore,this paper presents an energy-optimal braking strategy(EOBS)to improve the energy efficiency of EVs with the consideration of shared braking intention.First,a double-layer control scheme is formulated.In the upper-layer,an energy-optimal braking problem with accessed braking intention is formulated and solved by the distance-based dynamic programming algorithm,which could derive the energy-optimal braking trajectory.In the lower-layer,the nonlinear time-varying vehicle longitudinal dynamics is transformed to the linear time-varying system,then an efficient model predictive controller is designed and solved by quadratic programming algorithm to track the original energy-optimal braking trajectory while ensuring braking comfort and safety.Several simulations are conducted by jointing MATLAB and CarSim,the results demonstrated the proposed EOBS achieves prominent regeneration energy improvement than the regular constant deceleration braking strategy.Finally,the energy-optimal braking mechanism of EVs is investigated based on the analysis of braking deceleration,battery charging power,and motor efficiency,which could be a guide to real-time control.

Improving energy utilization efficiency of electrical discharge milling in titanium alloys machining

Electrical discharge milling(ED-milling) can be a good choice for titanium alloys machining and it was proven that its machining efficiency can be improved to compete with mechanical cutting. In order to improve energy utilization efficiency of ED-milling process, unstable arc discharge and stable arc discharge combined with normal discharge were implemented for material removal by adjusting servo control strategy. The influence of electrode rotating speed and dielectric flushing pressure on machining performance was investigated by experiments. It was found that the rotating of electrode could move the position of discharge plasma channel, and high pressure flushing could wash melted debris out the discharge gap effectively. Both electrode rotating motion and high pressure flushing are contributed to the improvement of machining efficiency.

Estimate of China's energy carbon emissions peak and analysis on electric power carbon emissions

China＇s energy carbon emissions are projected to peak in 2030 with approximately 110% of its 2020 level under the following conditions： 1） China＇s gross primary energy consumption is 5 Gtce in 2020 and 6 Gtce in 2030; 2） coal＇s share of the energy consumption is 61% in 2020 and 55% in 2030; 3） non-fossil energy＇s share increases from 15% in 2020 to 20% in 2030; 4） through 2030, China＇s GDP grows at an average annual rate of 6%; 5） the annual energy consumption elasticity coefficient is 0.30 in average; and 6） the annual growth rate of energy consumption steadily reduces to within 1%. China＇s electricity generating capacity would be 1,990 GW, with 8,600 TW h of power generation output in 2020. Of that output 66% would be from coal, 5% from gas, and 29% from non-fossil energy. By 2030, electricity generating capacity would reach 3,170 GW with 11,900 TW h of power generation output. Of that output, 56% would be from coal, 6% from gas, and 37% from non-fossil energy. From 2020 to 2030, CO2 emissions from electric power would relatively fall by 0.2 Gt due to lower coal consumption, and rela- tively fall by nearly 0.3 Gt with the installation of more coal-fired cogeneration units. During 2020--2030, the portion of carbon emissions from electric power in China＇s energy consumption is projected to increase by 3.4 percentage points. Although the carbon emissions from electric power would keep increasing to 118% of the 2020 level in 2030, the electric power industry would continue to play a decisive role in achieving the goal of increase in non-fossil energy use. This study proposes countermeasures and recommendations to control carbon emissions peak, including energy system optimization, green-coal-fired electricity generation, and demand side management.

Rational design of natural leather-based water evaporator for electricity generation and functional applications

In recent years,water evaporation-induced electricity has attracted a great deal of attention as an emerging green and renewable energy harvesting technology.Although abundant materials have been developed to fabricate hydrovoltaic devices,the limitations of high costs,inconvenient storage and transport,low environmental benefits,and unadaptable shape have restricted their wide applications.Here,an electricity generator driven by water evaporation has been engineered based on natural biomass leather with inherent properties of good moisture permeability,excellent wettability,physicochemical stability,flexibility,and biocompatibility.Including numerous nano/microchannels together with rich oxygen-bearing functional groups,the natural leather-based water evaporator,Leather_(Emblic-NPs-SA/CB),could continuously produce electricity even staying outside,achieving a maximum output voltage of∼3 V with six-series connection.Furthermore,the leather-based water evaporator has enormous potential for use as a flexible self-powered electronic floor and seawater demineralizer due to its sensitive pressure sensing ability as well as its excellent photothermal conversion efficiency(96.3%)and thus fast water evaporation rate(2.65 kg m^(−2)h^(−1)).This work offers a new and functional material for the construction of hydrovoltaic devices to harvest the sustained green energy from water evaporation in arbitrary ambient environments,which shows great promise in their widespread applications.

Techno-Economic Optimization of Novel Stand-Alone Renewable Based Electric Vehicle Charging Station near Bahria Town Karachi,Sindh Pakistan

Electric vehicles (EVs) are the most interesting and innovative technology in the 21st century because of theirenormous advantages, both technically and economically. Their emissions rate compared to fuel-based vehicles isnegligible as they do not consume fuel and hence do not emit any harmful gases. However, their bulk production,adoption and lack of charging stations increase the stress of power stations due to modern-day lifestyles. If Electricvehicles demand increases drastically then conventional power stations will not bear their demand and if theygenerate electricity by conventional means it will be very costly and may further add greenhouse gases. Therefore,this research provides the techno-economic assessment of a stand-alone renewable-dependent electric vehiclecharging station, excluding any burden on electrical utility. The proposed study is carried out in Bahria Town,Karachi, a city in Pakistan. In this study, HOMER Pro software was utilized for techno-economic assessment. Ahybrid system comprising solar Photovoltaic/Wind Turbine/Fuel cells and battery storage is included in the model.Solar and wind resources were taken from NASA’s website, where charging stations will be integrated. The overallresults show promising in terms of total Net Present Cost and the Cost of Energy which are 2.72M $ and 0.237 $,respectively. The total system generation is 3,598 Megawatt hours per year, and the total energy consumption is 885Megawatt hours per year.

Torsional vibration suppression and electromechanical coupling characteristics of electric drive system considering misalignment

The torque ripples resulting from external electromagnetic excitation and mechanical internal excitation contribute to significant torsional vibration issues within electromechanical coupling systems.To mitigate these fluctuations,a passive control strategy centered around a multi-stable nonlinear energy sink(MNES)is proposed.First,models for electromagnetic torque,gear nonlinear meshing torque,and misalignment torque are established.Building upon this foundation,an electromechanical coupling dynamic model of the electric drive system is formulated.Sensitivity analysis is conducted to determine the sensitive nodes of each mode and to provide guidance for the installation of the MNES.The structure of the MNES is introduced,and an electromechanical coupling dynamic model with the MNES is established.Based on this model,the influence of the misaligned angle on the electromechanical coupling characteristics is analyzed.In addition,the vibration suppression performance of the MNES is studied under both speed and uniform speed conditions.Finally,experimental testing is conducted to verify the vibration suppression performance of the MNES.The results indicate that misalignment triggers the emergence of its characteristic frequencies and associated sidebands.Meanwhile,the MNES effectively mitigates the torsional vibrations in the coupled system,demonstrating suppression rates of 52.69%in simulations and 63.3%in experiments.

DEVELOPMENT OF THE ENERGY MANAGEMENT STRATEGY FOR PARALLEL HYBRID ELECTRIC URBAN BUSES

A novel parallel hybrid electrical urban bus （PHEUB） configuration consisting of an extra one-way clutch and an automatic mechanical transmission （AMT） is taken as the study subject. An energy management strategy combining a logic threshold approach and an instantaneous optimization algorithm is proposed for the investigated PHEUB. The objective of the energy management strategy is to achieve acceptable vehicle performance and drivability requirements while simultaneously maximizing the engine fuel consumption and maintaining the battery state of charge in its operation range at all times. Under the environment of Matlab/Simulink, a computer simulation model for the PHEUB is constructed by using the model building method combining theoretical analysis and bench test data. Simulation and experiment results for China Typical Bus Driving Schedule at Urban District （CTBDS_UD） are obtained, and the results indicate that the proposed control strategy not only controls the hybrid system efficiently but also improves the fuel economy significantly.