<div class="section abstract"><div class="htmlview paragraph">Fuel economy and emission regulations for Light-duty Trucks (LDT) are becoming increasingly restrictive year by year. At the same time, Mid-size SUV demands are increasing all over the world. The advancement of Toyota Hybrid System (THS) aims to meet increasingly strict fuel economy regulations and rapidly advance vehicle technologies to meet electrification goals by 2050 (<span class="xref">Figure 1</span>). Toyota has been committed to the evolution of hybrid technology starting with the first Prius in 1997 and continues to develop industry leading electrification technologies. The updated hybrid system for the brand-new Highlander was developed to meet worldwide regulations and have competitive class leading fuel economy with an affordable price. This technology is necessary not only to anticipate expanding SUV sales around the world, but to also keep environmental impact to a minimum. This paper explains the performance and technology in the updated THS developed for the brand-new Highlander HV 2.5L E-Four and highlights environmental and performance comparisons to the MY2019 RAV4 HV and the previous generation Highlander HV.</div></div>

Widely published research shows that significant fuel economy improvements through optimal control of a vehicle powertrain are possible if the future vehicle velocity is known and real-time optimization calculations can be performed. In this research, however, we seek to advance the field of optimal powertrain control by limiting future vehicle operation knowledge and using no real-time optimization calculations. We have realized optimal control of acceleration events (AEs) in real-time by studying optimal control trends across 384 real world drive cycles and deriving an optimal control strategy for specific acceleration event categories using dynamic programming (DP). This optimal control strategy is then applied to all other acceleration events in its category, as well as separate standard and custom drive cycles using a look-up table. Fuel economy improvements of 2% average for acceleration events and 3.9% for an independent drive cycle were observed when compared to our rigorously validated 2010 Toyota Prius model. Our conclusion is that optimal control can be implemented in real-time using standard vehicle controllers assuming extremely limited information about future vehicle operation is known such as an approximate starting and ending velocity for an acceleration event.

System design tools including simulation and component optimization are an increasingly important component of the vehicle design process, placing more emphasis on early stages of design to reduce redesign and enable more robust design. This study focuses on the energy use and power management simulations used in vehicle design and optimization. Vehicle performance is most often evaluated in simulation, physical testing, and certification using drive cycle cases (also known as dynamometer schedules or drive schedules). In vehicle optimization studies, the information included in each drive cycle has been shown to influence the attributes of the optimized vehicle, and including more drive cycles in simulation optimizations has been shown to improve the robustness of the optimized design. This paper aims to quantitatively understand the effect of drive cycles on optimization in vehicle design and to specify drive cycles that can lead to robust vehicle design with minimal simulation. Two investigations are performed in service of this objective; investigation 1 tests how different combinations of drive cycles affect optimized vehicle performance and design variables (DV); investigation 2 evaluates the use of stochastic drive cycles for improving the robustness of vehicle designs without adding computational cost to the design and optimization process.

No abstract

No abstract