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Fuel consumption reduction on medium-duty tactical truck has and continues to be a significant initiative for the U.S. Army. The Crankshaft-Integrated-Starter-Generator (C-ISG) is one of the parallel hybrid propulsions to improve the fuel economy. The C-ISG configuration is attractive because one electric machine can be used to propel the vehicle, to start the engine, and to be function as a generator. The C-ISG has been implemented in one M1083A1 5-ton tactical cargo truck. This paper presents the experimental assessments of the C-ISG hybrid truck characteristics. The experimental assessments include all electric range for on- and off-road mission cycles and fuel consumption for the high voltage battery charging. Stationary tests related to the charging profile of the battery pack and the silent watch time duration is also conducted.

Lithium-ion polymer battery has been widely used for vehicle onboard electric energy storage ranging from 12V SLI (Starting, Lighting, and Ignition), 48V mild hybrid electric, to 300V battery electric vehicle. Formulation on cell parameters acquired from minimum numbers of experiments, the modeling and simulation could be an effective approach in predicting battery performance, thermal effectiveness, and degradation. This paper describes the modeling, simulation, and validation of Lithium-Nickel-Manganese-Cobalt-Oxide (LiNiMnCoO2) based cell with 3.6V nominal voltage and 20Ah capacity. Constant current 20A, 40A, 60A, and 80A discharge tests are conducted in the computer-controlled cycler and temperature chamber. Discharging voltage curves and cell surface temperature distributions are recorded in each discharging test. A three-dimensional cell model is constructed in the COMSOL multi-physics platform based on the cell parameters.

Battery temperature variations have a strong effect on both battery aging and battery performance. Significant temperature variations will lead to different battery behaviors. This influences the performance of the Hybrid Electric Vehicle (HEV) energy management strategies. This paper investigates how variations in battery temperature will affect Lithium-ion battery aging and fuel economy of a HEV. The investigated energy management strategy used in this paper is the Equivalent Consumption Minimization Strategy (ECMS) which is a well-known energy management strategy for HEVs. The studied vehicle is a Honda Civic Hybrid and the studied battery, a BLS LiFePO4 3.2Volts 100Ah Electric Vehicle battery cell. Vehicle simulations were done with a validated vehicle model using multiple combinations of highway and city drive cycles. The battery temperature variation is studied with regards to outside air temperature.

With the mass movement toward electrification and renewable technologies, the scope of innovation of electrification has gone beyond the automotive industry into areas such as electric motorcycle applications. This paper provides a discussion of the methodology and complexities of converting an internal combustion motorcycle to an electric motorcycle. In developing this methodology, performance goals including, speed limits, range, weight, charge times, as well as riding styles will be examined and discussed. Based on the goals of this paper, parts capable of reaching the performance targets are selected accordingly. Documentation of the build process will be presented along with the constraints, pitfalls, and difficulties associated with the process of the project. The step-by-step process that is developed can be used as a guideline for future build and should be used as necessary.

This paper considers optimal power management during the establishment of an expeditionary outpost using battery and vehicle assets for electrical generation. The first step in creating a new outpost is implementing the physical protection and barrier system. Afterwards, facilities that provide communications, fires, meals, and moral boosts are implemented that steadily increase the electrical load while dynamic events, such as patrols, can cause abrupt changes in the electrical load profile. Being able to create a fully functioning outpost within 72 hours is a typical objective where the electrical power generation starts with batteries, transitions to gasoline generators and is eventually replaced by diesel generators as the outpost matures. Vehicles with power export capability are an attractive supplement to this electrical power evolution since they are usually on site, would reduce the amount of material for outpost creation, and provide a modular approach to outpost build-up.

As vehicles are getting electrified and more intelligent, the energy consumption of the auxiliary system increases rapidly. The auxiliary battery acts as the backbone of the system to support the proper operation of the vehicle. It is important to ensure the auxiliary battery has enough energy to meet the basic loads regardless the vehicle is in park or running. However, the existing methods only focus on auxiliary energy management when the vehicle is in a dynamic event. To fulfill the gap, we propose an intelligent strategy that detects the low state of charge (SOC) condition, temporarily turns down the auxiliary loads based on their priorities and charges the auxiliary battery at the maximum efficiency of the auxiliary power unit. In addition, the proposed strategy allows the vehicle to get the park duration update and make intelligent decisions on charging the auxiliary battery.

This paper studies the hardware-in-the-loop (HiL) design of a power-split hybrid electric vehicle (HEV) for the research of HEV lithiumion battery aging. In this paper, an electrochemical model of a lithium-ion battery pack with the characteristics of battery aging is built and integrated into the vehicle model of Autonomie® software from Argonne National Laboratory. The vehicle model, together with the electrochemical battery model, is designed to run in a dSPACE real-time simulator while the powertrain power distribution is managed by a dSPACE MicroAutoBoxII hardware controller. The control interface is designed using dSPACE ControlDesk to monitor the real-time simulation results. The HiL simulation results with the performance of vehicle dynamics and the thermal aging of the battery are presented and analyzed.

Vehicle-to-Grid (V2G) service has a potential to improve the reliability and stability of the electrical grid due to the ability of providing bi-directional power flow from/to the grid. However, frequent charging/discharging may impact the battery lifetime. This paper presents the analysis of battery degradation in three scenarios. In the first scenario, different battery capacities are considered. In the second scenario, the battery degradation with various depth of discharge (DOD) are studied. In the third scenario, the capacity loss due to different charging regime are compared. The charging/discharging of plug-in electric vehicles (PEVs) are simulated in a single-phase microgrid system integrated with a photovoltaics (PV) farm, an energy storage system (ESS), and ten electric vehicle service equipment (EVSE). The battery degradation model is an energy throughput model, which is developed based on the Arrhenius equation and a power law relationship between time and capacity fading.

A high voltage battery is an essential part of hybrid electric vehicles (HEVs). It is imperative to precisely estimate the state of charge (SOC) and state of health (SOH) of battery in real time to maintain reliable vehicle operating conditions. This paper presents a method of estimating SOC and SOH through the incorporation of current integration, voltage translation, and Ah-throughput. SOC estimation utilizing current integration is inadequate due to the accumulation of errors over the period of usage. Thus voltage translation of SOC is applied to rectify current integration method which improves the accuracy of estimation. Voltage translation data is obtained by subjecting the battery to hybrid pulse power characterization (HPPC) test. The Battery State of Health was determined by semi-empirical model combined with accumulated Ah-throughput method. Battery state of charge was employed as an input to estimate damages accumulated to battery aging through a real-time model.

This paper studies the nonlinear model predictive control for a power-split Hybrid Electric Vehicle (HEV) power management system to improve the fuel economy. In this paper, a physics-based battery model is built and integrated with a base HEV model from Autonomie®, a powertrain and vehicle model architecture and development software from Argonne National Laboratory. The original equivalent circuit battery model from the software has been replaced by a single particle electrochemical lithium ion battery model. A predictive model that predicts the driver’s power request, the battery state of charge (SOC) and the engine fuel consumption is studied and used for the nonlinear model predictive controller (NMPC). A dedicated NMPC algorithm and its solver are developed and validated with the integrated HEV model. The performance of the NMPC algorithm is compared with that of a rule-based controller.

In this work, a pseudo three-dimensional coupled thermal-electrochemical model is established to estimate the heat generation and temperature profiles of a lithium ion battery as functions of the state of the discharge. Then, this model is used to investigate the effectiveness of active and passive thermal management systems. The active cooling system utilizes cooling plate and water as the working fluid while the passive cooling system incorporates a phase change material (PCM). The thermal effects of coolant flow rate examined using a computational fluid dynamics model. In the passive cooling system, Paraffin wax used as a heat dissipation source to control battery temperature rise. The effect of module size and battery spacing is studied to find the optimal weight of PCM required. The results show that although the active cooling system has the capability to reduce the peak temperatures, it leads to a large temperature difference over the battery module.

The Wayne State University (WSU) EcoCAR 2 Team designed the conversion of a GM donated 2013 Chevrolet Malibu to a Parallel-Through-The-Road (PTTR) Plug-In Hybrid vehicle within a 9 month timeframe. This fast prototyping project used the EcoCAR 2 Vehicle Development Process (EVDP). Various tradeoffs were made to meet all competition requirements and to make the vehicle as competitive as possible within budget, time and experience limitations. The chosen PTTR architecture, nicknamed by the team as “E2D2” (Ethanol-Electric Dual-Drivetrain), provides up to 35.7 electric only miles and a fuel economy of 60 miles per gallons gasoline equivalent (mpgge) or 3.96 liters gasoline equivalent (lge) per one hundred km. This is accomplished using an E85 engine-driven front traction system and a battery-electric-motors-driven rear traction system. The team developed the control system and designed the packaging and integration of all required components including the Energy Storage System (ESS).

The central performance requirement for electrochemical energy storage systems for the full power-assist hybrid electric vehicle (HEV) is pulse power capability, typically 25-40 kW pulse power capability for 10 seconds duration. Standard test procedures utilize constant current pulses. However, in the HEV application, the power transient for acceleration is a ramped power transient and the power transient for regenerative braking power is a descending power ramp. This paper compares the usable power capability of batteries and supercapacitors under constant current, constant power, and ramped power transients. Although the usable battery discharge power is relatively insensitive to the transient type applied, 10-40% higher regenerative braking charge capability is observed with ramped power transients. With supercapacitors, the discharge and charge capability is much more strongly dependent on the type of power transient.

Battery State of Charge (SOC) constraints are used to prevent the battery in Hybrid Electric Vehicles (HEVs) from over-charging or over-discharging. These constraints strongly influence the power-split of the HEV. This paper presents results on how Battery State of Charge (SOC) constraints effects Lithium ion battery aging and fuel economy when using the Equivalent Consumption Minimization Strategy (ECMS). The vehicle studied is the Honda Civic Hybrid. The battery used is A123 Systems’ ANR26650 battery cell. Vehicle simulation uses multiple combinations of highway and city drive cycles. For each combination of drive cycles, nine SOC constraints ranges are used. Battery aging is evaluated using a semi-empirical model combined with the accumulated Ah-throughput method which uses, as an input, the battery SOC trajectory from the vehicle simulations. The simulation results provide insight into how SOC constraints effect fuel economy as well as battery aging.

The Wayne State University (WSU) EcoCAR2 student team designed, modeled, Model-In-the-Loop (MIL) tested, Software-In-the-Loop (SIL) simulation tested, and Hardware-In-the-Loop (HIL) simulation tested the team's conversion design for taking a 2013 Chevrolet Malibu and converting it into a Parallel-Through-The-Road (PTTR) plug-in hybrid. The 2013 Malibu is a conventional Front Wheel Drive (FWD) vehicle and the team's conversion design keeps the conventional FWD and adds a Rear Wheel Drive (RWD) powertrain consisting of an electric motor, a single speed reduction gearbox and a differential to drive the rear wheels -where none of these previously existed on the rear wheels. The RWD addition creates the PTTR hybrid powertrain architecture of two driven axles where the mechanical torque path connection between the two powertrains is through the road, rather than a mechanical torque path through gears, chains, or shafts.

This paper investigates the aging performance of the lithium ion cobalt oxide battery pack of a single shaft parallel hybrid electric vehicle (HEV) under different ambient temperatures. Varying ambient temperature of HEVs results in different battery temperature and then leads to different aging performance of the battery pack. Battery aging is reflected in the increasing of battery internal resistance and the decreasing of battery capacity. In this paper, a single shaft parallel hybrid electric vehicle model is built by integrating Automotive Simulation Model (ASM) from dSPACE and AutoLion-ST battery model from ECPower to realize the co-simulation of HEV powertrain in the common MATLAB/Simulink platform. The battery model is a physics-based and thermally-coupled battery (TCB) model, which enables the investigation of battery capacity degradation and aging. Standard driving cycle with differing ambient temperatures is tested using developed HEV model.

Increasing regulatory demand to reduce CO2 emissions has led to an industry focus on electrified vehicles while limiting the development of conventional internal combustion engine (ICE) and hybrid powertrains. Hybrid electric vehicle (HEV) powertrains rely on conventional SI mode IC engines that are optimized for a narrow operating range. Advanced combustion strategies such as Gasoline Compression Ignition (GCI) have been demonstrated by several others including the authors to improve brake thermal efficiency compared to both gasoline SI and Diesel CI modes. Soot and NOx emissions are also reduced significantly by using gasoline instead of diesel in GCI engines due to differences in composition, fuel properties, and reactivity. In this work, an HEV system was proposed utilizing a multi-mode GCI based ICE combined with a HEV components (e-motor, battery, and invertor).

Extreme Fast Charging (XFC) infrastructure is crucial for an increase in electric vehicle (EV) adoption. However, an unmanaged implementation may lead to negative grid impacts and huge power costs. This paper presents an optimal energy management strategy to utilize grid-connected Energy Storage Systems (ESS) integrated with XFC stations to mitigate these grid impacts and peak demand charges. To achieve this goal, an algorithm that controls the charge and discharge of ESS based on an optimal power threshold is developed. The optimal power threshold is determined to carry out maximum peak shaving for given battery size and SOC constraints.

The Wayne State University student team reengineered a mid-sized sedan into a functional plug-in hybrid electric vehicle as participants in the EcoCAR 2 competition sponsored by the US Department of Energy and managed by Argonne National Laboratory. The competition goals included reducing petroleum usage, emissions, and energy consumption through implementing advanced vehicle technologies. During the competition, the team did plug-in charging of the 19 kWh high voltage traction battery, drove in pure electric mode (engine off) until the battery was depleted, then switched to hybrid mode and continued driving by using E85 from the fuel tank. The pure electric mode vehicle driving range was 48 km [30 miles] while pulling an emissions instrumented test trailer and projected to be 58 km [36 miles] without the test trailer load for the competition's city/highway blend drive cycle.

It is well known that thermal management is a key factor in design and performance analysis of Lithium-ion (Li-ion) battery, which is widely adopted for hybrid and electric vehicles. In this paper, an air cooled battery thermal management system design has been proposed and analyzed for mild hybrid vehicle application. Computational Fluid Dynamics (CFD) analysis was performed using CD-adapco's STAR-CCM+ solver and Battery Simulation Module (BMS) application to predict the temperature distribution within a module comprised of twelve 40Ah Superior Lithium Polymer Battery (SLPB) cells connected in series. The cells are cooled by air through aluminum cooling plate sandwiched in-between every pair of cells. The cooling plate has extended the cooling surface area exposed to cooling air flow. Cell level electrical and thermal simulation results were validated against experimental measurements.