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Toyota developed a new hybrid unit “L4A0” for the new Tundra, which creates both good drivability and environmental performance. To ensure off-road, towing performance and typical truck driving characteristics, the unit is based on a transmission with a torque converter and a multi-plate lock up clutch, with a motor-generator and K0 clutch installed between the engine and transmission. The motor-generator and K0 clutch are built into a module, making it possible to create new hybrid units by combining the module with various transmissions. The unit features many different motor controls. For example, in the case of step-in acceleration input, in order to achieve the desired output torque, typically a kick-down shift is necessary [1]; however, by utilizing “L4A0” both high response and high power output is achieved even without a kick-down shift. This is accomplished by assisting the engine with the motor-generator even when the engine torque is delayed at low engine speeds.

Real-world second-by-second vehicle driving cycle data is very important for vehicle research and development. A project solely dedicated to generating such information would be tremendously costly and time consuming. Alternatively, we developed such a database by utilizing two publicly available passenger vehicle travel surveys: 2004-2006 Puget Sound Regional Council (PSRC) Travel Survey and 2011 Atlanta Regional Commission (ARC) Travel Survey. The surveys complement each other - the former is in low time resolution but covers driver operation for over one year whereas the latter is in high time resolution but represents only one-week-long driving operation. After analyzing the PSRC survey, we chose 382 vehicles, each of which continuously operated for one year, and matched their trips to all the ARC trips. The matching is carried out based on trip distance first, then on average speed, and finally on duration.

The development of electric vehicles has been progressed, rapidly, to achieve Carbon neutrality by 2050. There have been increasing concerns about Electromagnetic Compatibility (EMC) performance due to increasing power for power trains of vehicles. Because same power train system expands to some vehicles, we have developed numerical simulations in order to predict the vehicle EMC performances. We modeled a vehicle which has inverter noises by numerical simulation to calculate electric fields based on GB/T18387. We simulated the common mode noise which flows through the shielding braid of the high voltage wire harnesses. As a result, it is confirmed a correlation between the electric fields calculated by numerical simulation and the measured one.

It is an important factor in electric vehicles to show customers how much they can drive with the energy of the remaining battery. If the remaining mileage is not accurate, electric vehicle drivers will have no choice but have to feel anxious about the mileage. Additionally, the potential customers have range anxiety when they consider Electric Vehicles. If the remaining mileage to drive is wrong, drivers may not be able to get to the charging station and may not be able to drive because the battery runs out. It is important to show the remaining available driving range exactly for drivers. The previous study proposed an advanced model by predicting the remaining mileage based on actual driving data and based on reflecting the pattern of customers who drive regularly. The Bayesian linear regression model was right model in previous study.

Recently, as part of the effort to enhance fuel efficiency and reduce costs for eco-friendly vehicles, the R-gearless system has been implemented in the TMED (P)HEV system. Due to the removal of the reverse gear, a distinct backward driving method needs to be developed, allowing the Electronic Motor (e-Motor) system to facilitate backward movement in the TMED (P)HEV system. However, the capability of backward driving with the e-Motor is limited because of partial failure in the high-voltage system of an R-gearless system. Thus, we demonstrate that it is possible to improve backward driving problems by applying a new fail-safe strategy. In the event of a high-voltage battery system failure, backward driving can be achieved using the e-Motor with constant voltage control by the Hybrid Starter Generator (HSG), as proposed in this study.

To adapt to Battery Electric Vehicle (BEV) integration, the significance of protective designs for battery packs against ground impact caused by road debris is very high, and there is also a keen interest in the feasibility assessment technique using Computer-Aided Engineering (CAE) tools for prototype-free evaluations. However, the challenge lies in obtaining real-world empirical data to verify the accuracy of the predictive CAE model. Collecting real-world data using actual battery pack can be time-consuming, costly, and accurately ascertaining the precise direction, magnitude, and location of the force applied from the road to the battery pack poses a challenging task. Therefore, in this study, we developed a methodology using machine learning, specifically Gaussian process regression (GPR), to perform inverse analysis of the direction, magnitude, and location of vehicle-road contact forces during rough road conditions.

Recently, regulations on automobile emission have been significantly strengthened to address climate change. The automobile industry is responding to these regulations by developing electric vehicles that use batteries and fuel-cells. Automobile emissions are environmentally harmful, especially in the case of vehicles equipped with high-temperature and high-pressure diesel engines using compression-ignition, the proportion of nitrogen oxides (NOx) emissions reaches as high as 85%. Additionally, air pollution caused by particulate matter (PM) is six to ten times higher compared to gasoline engines. Therefore, the electrification of commercial vehicles using diesel engines could potentially yield even greater environmental benefits. For commercial vehicles battery electric vehicles (BEVs) require a large number of batteries to secure a long driving range, which reduces their maximum payload capacity.

Despite the widespread adoption of lithium-ion batteries in various applications such as energy storage, concerns related to thermal management have been persisting, primarily due to the heat generated during their operation and the associated adverse effects on its efficiency, safety, and lifetime. Hence, the thermal characterization of lithium-ion batteries is essential for optimizing the layout of the battery cells for a pack design and the corresponding thermal management system. This study focuses on an experimental investigation of heat generation of Li-ion batteries under different operating conditions, including charge-discharge rates, ambient temperatures, states of charge, and compressive pressure. The experiments were conducted using a custom-designed multifunctional calorimeter, enabling precise measurement of the heat generation rate of the battery and the entropy coefficient. The measured results have shown a good match with the calculated heat generation rate.

It is necessary for us to reduce CO2 emissions in order to hold down global warming which is advancing year by year. Toyota Motor Corporation believes that not only the introduction of BEVs but also the sale of the hybrid vehicles must spread in order to achieve the necessary CO2 reduction. Therefore, we planned to improve the attractiveness of future hybrid vehicles. Prius has always made full use of hybrid technologies and leading to significant CO2 reduction. Toyota Motor Corporation has developed a 2.0L hybrid system for the new Prius. We built the system which could achieve a comfortable drive along following the customer’s intention while improving the fuel economy more than a conventional system. The engine improves on both output and thermal efficiency. The transaxle decreases mechanical loss by downsizing the differential, and adoption of low viscosity oil.

In recent years, electrically heated catalysts (EHCs) have been developed to achieve lower emissions. In several EHC heating methods, the direct heating method, which an electric current is applied directly to the catalyst substrate, can easily activate the catalyst before engine start-up. The research results reported on the use of the direct heating EHC to achieve significant exhaust gas purification during cold start-up [1]. From the perspective of catalyst loading, ceramics is considered to be a better material for the substrate than metal due to the difference in coefficient of thermal expansion between the catalyst and the substrate, but the EHC made of ceramics has difficulties such as controllability of the current distribution, durability and reliability of the connection between the substrate and the electrodes.

For energy saving and global warming prevention, Toyota has developed Toyota Hybrid System (THS) for mass-produced passenger cars, which achieves drastic improvement in fuel efficiency and reduction in exhaust emissions compared to conventional gasoline engine cars. The THS has two motive power sources which engage depending on driving conditions. It's power is supplied either from an engine (controlled by the engine ECU) or an electric motor (controlled by the motor ECU) which is powered by a high-voltage battery (monitored by the battery ECU). These ECUs are controlled by a hybrid ECU. Each ECU has been developed with a fail-safe system in mind, to ensure driver safety in case of vehicle breakdowns. Among these ECUs, this paper reports particularly on the newly introduced ECUs: hybrid ECU and battery ECU. In the development of these ECUs, special attention was focused on fail-safe performance.

It is known that the collisions caused by lane departure events account for range of percentages among the countries studied. To help prevent such collisions, the Lane Departure Warning (LDW) system has started to be introduced in production vehicles, but there is little research on its benefits and limitations so far. In this paper we performed an in-depth analysis of the collisions and driver-related essential variables for the lane-departure collision scenarios and demonstrated the benefit estimation process. The benefit of the LDW system is estimated by comparing lane departure events when the vehicle has no LDW, and how they change with the addition of LDW. The event without LDW was modeled in 5 phases: (1) before departure, (2) starting of the departure, (3) departed the lane, (4) at the impact with an object, and, (5) after the impact. “An extensive analysis was conducted of traffic crash data compiled by the Institute for Traffic Accident Research and Data Analysis (ITARDA).

Reducing vehicle CO2 emissions is an important measure to help address global warming. To reduce CO2 emissions on a global basis, Toyota Motor Corporation is taking a multi-pathway approach that involves the introduction of the optimal powertrains according to the circumstances of each region, including hybrid electric (HEVs) and plug-in hybrid electric vehicles (PHEVs), as well as battery electric vehicles (BEVs). This report describes the development of a new PHEV system for the Toyota Prius. This system features a traction battery pack structure, transaxle, and power control unit (PCU) with boost converter, which were newly developed based on the 2.0-liter HEV system. As a result, the battery capacity was increased by 1.5 times compared to the previous model with almost the same battery pack size. Transmission efficiency was also improved, extending the distance that the Prius can be driven as an EV by 70%.

Mechanical shock tests for lithium metal and lithium-ion batteries often require that each cell or battery pack be subjected to multiple shocks in the positive and negative directions, of three mutually perpendicular orientations. This paper focuses on the no-disassembly requirement of those testing conditions and on the CAE methodology specifically developed to perform this assessment. Ford Motor Company developed a CAE analysis method to simulate this type of test and assess the possibility of cell dislodging. This CAE method helps identify and diagnose potential failure modes, thus guiding the Design Team in developing a strategy to meet the required performance under shock test loads. The final CAE-driven design focuses on the structural requirement and optimization, and leads to cost savings without compromising cell or pack mechanical performance.