Proton Holdings Berhad (PHB; informally Proton) is a Malaysian automotive company and automobile corporation active in automobile design, manufacturing, distribution and sales. Proton was established in 1983 as Malaysia's sole national badged car company until the advent of Perodua in 1993. The company is headquartered in Shah Alam, Selangor, and operates additional facilities at Proton City, Perak. 'Proton' is a Bahasa Malaysia acronym for Perusahaan Otomobil Nasional (National Automobile Company). Proton was originally a manufacturer of rebadged Mitsubishi Motors (MMC) products in the 1980s and 1990s. Proton produced its first indigenously designed (though Mitsubishi-engined), non-badge engineered car in the year 2000, and elevated Malaysia as the 11th country in the world with the capability to design cars from the ground up. Since the 2000s, Proton has produced a mix of locally engineered and badge engineered vehicles. Proton cars are currently sold in at least 15 countries, the majority of which are in Asia. Proton was originally owned in majority by HICOM, with minority stakes being held by Mitsubishi Group members. By 2005, Mitsubishi had divested their stake in Proton to Khazanah Nasional, and in 2012, Proton was fully acquired by DRB-HICOM. Proton was the owner of Lotus Cars from 1996 to 2017. In May 2017, DRB-HICOM announced plans to sell a 49.9% stake in Proton and a 51% stake in Lotus to Geely Automobile Holdings. The deal was signed in June 2017, and since then, Lotus ceased to be a unit of Proton.On 29 September 2017, DRB-HICOM announced changes to the board of Proton Holdings Berhad. Following the signing of a Definitive Agreement with China's Zhejiang Geely Holding Group Limited on 23 June 2017, the Chinese carmaker acquired 49.9% equity in Proton. The announcement on 29 September saw a new board of directors put in place in Proton Holdings, Proton Edar (the local distribution arm) and Perusahaan Otomobil Nasional Sdn Bhd (PONSB). Three nominees from Geely Holding joined the boards; Daniel Donghui Li, the Executive VP and CFO of Geely Holding; Dr Nathan Yuning, the Executive VP of International Business of Geely Holding, and Feng Qing Feng, the Group VP and CTO at HK-listed Geely Auto. DRB-HICOM are represented by Dato' Sri Syed Faisal Albar, who chairs the boards, and Amalanathan Thomas and Shaharul Farez Hassan. Both are part of the senior management team at DRB-HICOM. Also named on the same day was Dr Li Chunrong, who joins PONSB as CEO. Dr Li is the third foreigner to head Proton. Between 1993 and 1997, the early years of Proton, two different Japanese nominees of their-then partners, Mitsubishi Motors Corporation, helmed the carmaker. Proton, predominantly reliant on its domestic market, is presently undergoing a transformation process as part of a long-term turnaround plan, with hopes of returning to profitability and regaining an international presence. Proton's tie up with Geely is expected to put the company back on track with the introduction of the much-awaited SUV named Boyue touted to go on sale by end of 2018.
This SAE Edge Research Report explores advancements in next-generation mobility, focusing on digitalized and smart cockpits and cabins. It offers literature review, examining current customer experiences with traditional vehicles and future mobility expectations. Key topics include integrating smart cockpit and cabin technologies, addressing challenges in customer and user experience (UX) in digital environments, and discussing strategies for transitioning from traditional vehicles to electric ones while educating customers. User Experience for Digitalized and Smart Cockpits and Cabins of Next-gen Mobility covers both on- and off-vehicle experiences, analyzing complexities in developing and deploying digital products and services with effective user interfaces. Emphasis is placed on meeting UX requirements, gaining user acceptance, and avoiding trust issues due to poor UX. Additionally, the report concludes with suggestions for improving UX in digital products and services for future mobility, offering a summary of insights and actionable recommendations to enhance the UX in automotive technologies. Understanding the correlation between UX, user acceptance, and market success from a UX, design, and human-factor perspective will assist companies in creating customer-facing next-gen products. Click here to access the full SAE EDGETM Research Report portfolio.
The next generation of mobility, driven by shared, driverless, connected, and electrified vehicles, holds strong potential to advance sustainability through lower emissions and improved resource efficiency. However, critical questions remain regarding their true environmental impact, including battery lifecycle management, material consumption, and circular manufacturing practices. Sustainable Circular Future Mobility: Environmental Impact of Next-gen Vehicles explores these unresolved issues, focusing on the shift from internal combustion to electric vehicles, supply chain challenges, regulatory gaps, and the operational realities of sustainable productization. It also critically examines the risks of greenwashing, the need for consistent standards, and the role of intersectoral collaboration—with energy, urban planning, information and communications technologies, and waste management sectors—in building resilient, scalable solutions. The report provides strategic recommendations and actionable solutions to help stakeholders better navigate the transition toward a circular future for mobility. It further highlights the overlooked complexities in the Global South, emphasizing the importance of ethical market expansion and localized mobility strategies. Click here to access the full SAE EDGETM Research Report portfolio.
By understanding the implications of real-world driving conditions, improved fuel economy via a strategy of key technologies can be implemented to assist fuel economy validation during development programs. Vehicles in real-world driving conditions regularly travel at idle, low and medium speeds, particularly for urban driving, and this has a crucial weight in overall vehicle fuel economy, given the residencies at the lower engine speed and load region. This paper presents the validation of the derived engine conditions representing Malaysian actual urban driving in an attempt to formulate representative fuel economy data. The measurements were conducted through on-road urban driving within Kuala Lumpur to establish representative driving conditions. The effectiveness of the proposed conditions was then validated in terms of fuel economy using a simulation. The discrepancy between the fuel economy in the proposed conditions and the real-world measurements has improved, falling to 11.9% compared to 43.1% reported by the NEDC.
The design of a vehicle suspension system through simulation requires accurate representation of the design parameters. These parameters are usually difficult to measure or sometimes unavailable. This article proposes an efficient approach to identify the unknown parameters through optimization based on experimental results, where the covariance matrix adaptation-evolutionary strategy (CMA-es) is utilized to improve the simulation and experimental results against the kinematic and compliance tests. This speeds up the design and development cycle by recovering all the unknown data with respect to a set of kinematic measurements through a single optimization process. A case study employing a McPherson strut suspension system is modelled in a multi-body dynamic system. Three kinematic and compliance tests are examined, namely, vertical parallel wheel travel, opposite wheel travel and single wheel travel. The problem is formulated as a multi-objective optimization problem with 40 objectives and 49 design parameters. A hierarchical clustering method based on global sensitivity analysis is used to reduce the number of objectives to 30 by grouping correlated objectives together. Then, a dynamic summation of rank value is used as pseudo-objective functions to reformulate the multi-objective optimization to a single-objective optimization problem. The optimized results show a significant improvement in the correlation between the simulated model and the experimental model. Once accurate representation of the vehicle suspension model is achieved, further analysis, such as ride and handling performances, can be implemented for further optimization.
Emissions from motor vehicles are known to be the major contributor of air pollution. Pollutants that are commonly concerned and regulated for petrol engines are Hydrocarbons, Carbon Monoxide, Nitrogen Oxides and Particulate Matter. One of the most important factor that vary these pollutants is the engine operating condition such as cold start, low engine loads and high engine loads which are found during actual driving. In actual driving conditions, particularly in urban areas, vehicles regularly travel at idle, low or medium speeds which signify the engine part load operations. Thus urban driving carries a crucial weight on the overall vehicle fuel economy. Understanding the implications of urban driving conditions on fuel economy will allow for trategic application of key technologies such as cylinder deactivation in the efforts towards better efficiency. This paper presents the measurement and analysis of engine condition during Malaysian actual urban driving in an attempt to formulate representable fuel consumption data. The measurements were conducted through multiple on-road urban driving with an instrumented 1.6 litre car. Data was collected using the “chase” technique. Driving conditions were recorded over different routes within the selected urban areas, with considerations on the level of population, density and traffic congestion. The on-road driving was performed to measure vehicle speed, engine speed, accelerator pedal traces, engine torque and fuel consumption. The fact that high traffic congestion in urban area dictates the vehicle movements and the engine running conditions were analysed by clustering the variables. The analyses show that idling and cyclic speed ranging up to 25km/h were the most frequent conditions captured in the Malaysian urban driving. Using the cluster analysis, 10 important conditions were identified in developing a framework for the Malaysian actual urban driving conditions, towards representable fuel economy analysis.
